{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\User\Downloads\coronavirusstatelaws\205analysis_output20200330.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}30 Mar 2020, 23:14:44
{txt}
{com}. 
. *DESCRIPTIVES
. drop _all
{txt}
{com}. use $nfile
{txt}
{com}. foreach v of local vs {c -(}
{txt}  2{com}. di "DESCRIPTIVES OF `v' FOLLOW"
{txt}  3{com}. tab `v' gov if date>226&date<327
{txt}  4{com}. {c )-}
DESCRIPTIVES OF soemergency FOLLOW

     {txt}(sum) {c |}
soemergenc {c |}        gov_dem
         y {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       390        342 {txt}{c |}{res}       732 
{txt}         1 {c |}{res}        24         20 {txt}{c |}{res}        44 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       414        362 {txt}{c |}{res}       776 
DESCRIPTIVES OF natguard FOLLOW

     {txt}(sum) {c |}        gov_dem
  natguard {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       608        555 {txt}{c |}{res}     1,163 
{txt}         1 {c |}{res}        14         11 {txt}{c |}{res}        25 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       622        566 {txt}{c |}{res}     1,188 
DESCRIPTIVES OF stayathome FOLLOW

     {txt}(sum) {c |}        gov_dem
stayathome {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       736        637 {txt}{c |}{res}     1,373 
{txt}         1 {c |}{res}         5         14 {txt}{c |}{res}        19 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       741        651 {txt}{c |}{res}     1,392 
DESCRIPTIVES OF gather FOLLOW

     {txt}(sum) {c |}        gov_dem
    gather {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       687        600 {txt}{c |}{res}     1,287 
{txt}         1 {c |}{res}        13         18 {txt}{c |}{res}        31 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       700        618 {txt}{c |}{res}     1,318 
DESCRIPTIVES OF bars FOLLOW

           {txt}{c |}        gov_dem
(sum) bars {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       578        510 {txt}{c |}{res}     1,088 
{txt}         1 {c |}{res}        21         21 {txt}{c |}{res}        42 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       599        531 {txt}{c |}{res}     1,130 
DESCRIPTIVES OF school FOLLOW

     {txt}(sum) {c |}        gov_dem
    school {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       484        418 {txt}{c |}{res}       902 
{txt}         1 {c |}{res}        22         22 {txt}{c |}{res}        44 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       506        440 {txt}{c |}{res}       946 
DESCRIPTIVES OF ui FOLLOW

           {txt}{c |}        gov_dem
  (sum) ui {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       650        557 {txt}{c |}{res}     1,207 
{txt}         1 {c |}{res}        15         16 {txt}{c |}{res}        31 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       665        573 {txt}{c |}{res}     1,238 
DESCRIPTIVES OF childcare FOLLOW

     {txt}(sum) {c |}        gov_dem
 childcare {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       705        643 {txt}{c |}{res}     1,348 
{txt}         1 {c |}{res}        10          9 {txt}{c |}{res}        19 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       715        652 {txt}{c |}{res}     1,367 
DESCRIPTIVES OF eviction FOLLOW

     {txt}(sum) {c |}        gov_dem
  eviction {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       704        623 {txt}{c |}{res}     1,327 
{txt}         1 {c |}{res}         7         10 {txt}{c |}{res}        17 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       711        633 {txt}{c |}{res}     1,344 
{txt}
{com}. foreach x in gov stategdp per100k neighbor pop65 popcon2016 hospitalbeds2018 time timesq weekend black2018 hisp2018 {c -(}
{txt}  2{com}. di "DESCRIPTIVES OF `x' FOLLOW"
{txt}  3{com}. bysort gov: sum `x' if date>226&date<327
{txt}  4{com}. {c )-}
DESCRIPTIVES OF gov FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}gov {c |}{res}        754           0           0          0          0

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}gov {c |}{res}        696           1           0          1          1

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}gov {c |}{res}          0

DESCRIPTIVES OF stategdp FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}stategdp {c |}{res}        754    2.073077    .7029661         .5          4

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}stategdp {c |}{res}        696    1.845833    .7376298          0        3.1

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}stategdp {c |}{res}          0

DESCRIPTIVES OF per100k FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}per100k {c |}{res}        754    1.193041    2.510463          0   26.66665

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}per100k {c |}{res}        696    2.996999    10.71828          0   158.3823

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}per100k {c |}{res}          0

DESCRIPTIVES OF neighbor FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}neighbor {c |}{res}        754    4.417575     14.0258          0   158.3823

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}neighbor {c |}{res}        696    5.219549    17.12032          0   158.3823

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}neighbor {c |}{res}          0

DESCRIPTIVES OF pop65 FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}pop65 {c |}{res}        754      .21401    .0231654    .164664   .2584493

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}pop65 {c |}{res}        696    .2145161    .0225966   .1830176   .2575942

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}pop65 {c |}{res}          0

DESCRIPTIVES OF popcon2016 FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}popcon2016 {c |}{res}        754     .192953    .2219431          0   .7948525

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}popcon2016 {c |}{res}        696    .3105029    .2340524          0          1

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}popcon2016 {c |}{res}          0

DESCRIPTIVES OF hospitalbeds2018 FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
hospita~2018 {c |}{res}        754    2.826923    .7808324        1.8        4.8

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
hospita~2018 {c |}{res}        696    2.354167    .5167523        1.6        3.3

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
hospita~2018 {c |}{res}          0

DESCRIPTIVES OF time FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}time {c |}{res}        754          14    8.372154          0         28

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}time {c |}{res}        696          14    8.372617          0         28

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}time {c |}{res}          0

DESCRIPTIVES OF timesq FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}timesq {c |}{res}        754         266    242.6192          0        784

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}timesq {c |}{res}        696         266    242.6326          0        784

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}timesq {c |}{res}          0

DESCRIPTIVES OF weekend FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}weekend {c |}{res}        754    .2758621    .4472443          0          1

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}weekend {c |}{res}        696    .2758621    .4472691          0          1

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}weekend {c |}{res}          0

DESCRIPTIVES OF black2018 FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}black2018 {c |}{res}        754    .1271891    .1088179   .0144037   .3858193

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}black2018 {c |}{res}        696    .1185982    .0804847   .0113028   .3372396

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}black2018 {c |}{res}          0

DESCRIPTIVES OF hisp2018 FOLLOW

{txt}{hline}
-> gov = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}hisp2018 {c |}{res}        754    .1039991    .0913606   .0177719   .4021147

{txt}{hline}
-> gov = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}hisp2018 {c |}{res}        696    .1530509    .1144749   .0184122   .5026171

{txt}{hline}
-> gov = .

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}hisp2018 {c |}{res}          0

{txt}
{com}. 
. *MULTIVARIATE ANALYSES
. 
. *CORE MODEL
. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. logit `v' i.gov stategdp per100k neighbor pop65 popcon2016 hospitalbeds2018 time timesq weekend black2018 hisp2018 if date>226&date<327
{txt}  4{com}. margins gov if date==326, atmeans
{txt}  5{com}. predict pred`v'
{txt}  6{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-169.00668}  
Iteration 1:{space 3}log likelihood = {res:-146.79984}  
Iteration 2:{space 3}log likelihood = {res:-138.29115}  
Iteration 3:{space 3}log likelihood = {res:-137.32547}  
Iteration 4:{space 3}log likelihood = {res:-137.23715}  
Iteration 5:{space 3}log likelihood = {res:-137.23473}  
Iteration 6:{space 3}log likelihood = {res:-137.23472}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       776
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     63.54
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-137.23472{txt}{col 49}Pseudo R2{col 67}= {res}    0.1880

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     soemergency{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2} .0776082{col 30}{space 2} .3777916{col 41}{space 1}    0.21{col 50}{space 3}0.837{col 58}{space 4}-.6628498{col 71}{space 3} .8180662
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0330846{col 30}{space 2} .2939698{col 41}{space 1}   -0.11{col 50}{space 3}0.910{col 58}{space 4}-.6092548{col 71}{space 3} .5430855
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-1.231852{col 30}{space 2} .9150097{col 41}{space 1}   -1.35{col 50}{space 3}0.178{col 58}{space 4}-3.025238{col 71}{space 3} .5615336
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0606375{col 30}{space 2} .1573311{col 41}{space 1}   -0.39{col 50}{space 3}0.700{col 58}{space 4}-.3690007{col 71}{space 3} .2477258
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 1.694398{col 30}{space 2} 9.091354{col 41}{space 1}    0.19{col 50}{space 3}0.852{col 58}{space 4}-16.12433{col 71}{space 3} 19.51313
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.2869501{col 30}{space 2} .9489784{col 41}{space 1}   -0.30{col 50}{space 3}0.762{col 58}{space 4}-2.146914{col 71}{space 3} 1.573013
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2503123{col 30}{space 2} .3221028{col 41}{space 1}   -0.78{col 50}{space 3}0.437{col 58}{space 4}-.8816221{col 71}{space 3} .3809976
{txt}{space 12}time {c |}{col 18}{res}{space 2} .5386368{col 30}{space 2} .2085978{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4} .1297926{col 71}{space 3}  .947481
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0111601{col 30}{space 2} .0096404{col 41}{space 1}   -1.16{col 50}{space 3}0.247{col 58}{space 4}-.0300549{col 71}{space 3} .0077347
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.6112743{col 30}{space 2} .4353177{col 41}{space 1}   -1.40{col 50}{space 3}0.160{col 58}{space 4}-1.464481{col 71}{space 3} .2419328
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2}-.4399585{col 30}{space 2} 1.851538{col 41}{space 1}   -0.24{col 50}{space 3}0.812{col 58}{space 4}-4.068907{col 71}{space 3}  3.18899
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} 2.724347{col 30}{space 2}   1.9021{col 41}{space 1}    1.43{col 50}{space 3}0.152{col 58}{space 4}-1.003702{col 71}{space 3} 6.452395
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-6.470925{col 30}{space 2} 2.855357{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4}-12.06732{col 71}{space 3}-.8745283
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 2 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}         6
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(soemergency), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 3}.3333333 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 3}.6666667 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 8}1.8 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 4}9.09549 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}39.76911 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2095766 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.3892961 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 3}2.533333 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1499081 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.0978281 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} 8.28e-07{col 26}{space 2} 6.15e-06{col 37}{space 1}    0.13{col 46}{space 3}0.893{col 54}{space 4}-.0000112{col 67}{space 3} .0000129
{txt}{space 10}1  {c |}{col 14}{res}{space 2} 8.95e-07{col 26}{space 2} 6.62e-06{col 37}{space 1}    0.14{col 46}{space 3}0.892{col 54}{space 4}-.0000121{col 67}{space 3} .0000139
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(soemergency))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-121.26385}  
Iteration 1:{space 3}log likelihood = {res:-107.13547}  
Iteration 2:{space 3}log likelihood = {res: -98.49475}  
Iteration 3:{space 3}log likelihood = {res:-97.337087}  
Iteration 4:{space 3}log likelihood = {res:-97.290074}  
Iteration 5:{space 3}log likelihood = {res:-97.289925}  
Iteration 6:{space 3}log likelihood = {res:-97.289925}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,188
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     47.95
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-97.289925{txt}{col 49}Pseudo R2{col 67}= {res}    0.1977

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        natguard{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2}-.6934757{col 30}{space 2} .4910749{col 41}{space 1}   -1.41{col 50}{space 3}0.158{col 58}{space 4}-1.655965{col 71}{space 3} .2690133
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.1872085{col 30}{space 2} .4039515{col 41}{space 1}   -0.46{col 50}{space 3}0.643{col 58}{space 4}-.9789389{col 71}{space 3} .6045219
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0710847{col 30}{space 2} .1574958{col 41}{space 1}   -0.45{col 50}{space 3}0.652{col 58}{space 4}-.3797708{col 71}{space 3} .2376014
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0338633{col 30}{space 2} .0787791{col 41}{space 1}   -0.43{col 50}{space 3}0.667{col 58}{space 4}-.1882675{col 71}{space 3} .1205409
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 10.11523{col 30}{space 2} 13.23307{col 41}{space 1}    0.76{col 50}{space 3}0.445{col 58}{space 4}-15.82111{col 71}{space 3} 36.05156
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} 1.943738{col 30}{space 2} 1.043406{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4}-.1012993{col 71}{space 3} 3.988775
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0193244{col 30}{space 2} .4404056{col 41}{space 1}    0.04{col 50}{space 3}0.965{col 58}{space 4}-.8438547{col 71}{space 3} .8825035
{txt}{space 12}time {c |}{col 18}{res}{space 2} .7264167{col 30}{space 2} .2840318{col 41}{space 1}    2.56{col 50}{space 3}0.011{col 58}{space 4} .1697246{col 71}{space 3} 1.283109
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0163251{col 30}{space 2} .0088149{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4} -.033602{col 71}{space 3} .0009518
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.6797408{col 30}{space 2} .5619978{col 41}{space 1}   -1.21{col 50}{space 3}0.226{col 58}{space 4}-1.781236{col 71}{space 3} .4217546
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2}  8.52737{col 30}{space 2} 2.346387{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4} 3.928537{col 71}{space 3}  13.1262
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} 4.863329{col 30}{space 2} 2.576833{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.1871706{col 71}{space 3} 9.913829
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-14.19207{col 30}{space 2} 4.388336{col 41}{space 1}   -3.23{col 50}{space 3}0.001{col 58}{space 4}-22.79305{col 71}{space 3}-5.591094
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}        25
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(natguard), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 8}.48 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 8}.52 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 6}1.968 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}8.027461 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 4}27.1774 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2174264 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.1776697 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 6}2.664 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.0822299 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.1091255 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0091699{col 26}{space 2} .0141968{col 37}{space 1}    0.65{col 46}{space 3}0.518{col 54}{space 4}-.0186553{col 67}{space 3} .0369951
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0046046{col 26}{space 2}  .007103{col 37}{space 1}    0.65{col 46}{space 3}0.517{col 54}{space 4}-.0093171{col 67}{space 3} .0185263
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(natguard))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.45684}  
Iteration 1:{space 3}log likelihood = {res:-78.545496}  
Iteration 2:{space 3}log likelihood = {res:-67.889615}  
Iteration 3:{space 3}log likelihood = {res:-66.358542}  
Iteration 4:{space 3}log likelihood = {res: -63.59044}  
Iteration 5:{space 3}log likelihood = {res:-61.583178}  
Iteration 6:{space 3}log likelihood = {res:-61.047815}  
Iteration 7:{space 3}log likelihood = {res:-61.044944}  
Iteration 8:{space 3}log likelihood = {res:-61.044944}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,392
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     78.82
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-61.044944{txt}{col 49}Pseudo R2{col 67}= {res}    0.3923

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      stayathome{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2} 1.355048{col 30}{space 2} .6206373{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .1386217{col 71}{space 3} 2.571475
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.8223415{col 30}{space 2} .4918441{col 41}{space 1}   -1.67{col 50}{space 3}0.095{col 58}{space 4}-1.786338{col 71}{space 3} .1416552
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0097034{col 30}{space 2} .0193654{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.0476589{col 71}{space 3} .0282521
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0000735{col 30}{space 2} .0106105{col 41}{space 1}    0.01{col 50}{space 3}0.994{col 58}{space 4}-.0207226{col 71}{space 3} .0208697
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-12.01236{col 30}{space 2} 14.77881{col 41}{space 1}   -0.81{col 50}{space 3}0.416{col 58}{space 4}-40.97829{col 71}{space 3} 16.95357
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-2.175161{col 30}{space 2} 1.351296{col 41}{space 1}   -1.61{col 50}{space 3}0.107{col 58}{space 4}-4.823652{col 71}{space 3} .4733303
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.7613437{col 30}{space 2} .4932141{col 41}{space 1}   -1.54{col 50}{space 3}0.123{col 58}{space 4}-1.728026{col 71}{space 3} .2053382
{txt}{space 12}time {c |}{col 18}{res}{space 2} 8.106108{col 30}{space 2} 3.240145{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} 1.755539{col 71}{space 3} 14.45668
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.1597168{col 30}{space 2} .0664333{col 41}{space 1}   -2.40{col 50}{space 3}0.016{col 58}{space 4}-.2899237{col 71}{space 3}-.0295099
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.8559048{col 30}{space 2} .6888735{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-2.206072{col 71}{space 3} .4942625
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2}-4.093764{col 30}{space 2} 3.666927{col 41}{space 1}   -1.12{col 50}{space 3}0.264{col 58}{space 4}-11.28081{col 71}{space 3} 3.093281
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} 1.132938{col 30}{space 2} 2.776982{col 41}{space 1}    0.41{col 50}{space 3}0.683{col 58}{space 4}-4.309847{col 71}{space 3} 6.575722
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-98.58324{col 30}{space 2} 39.52829{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-176.0573{col 71}{space 3}-21.10921
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 808 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}        32
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(stayathome), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 5}.65625 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 5}.34375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 4}2.04375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}13.02696 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}32.34745 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2143136 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.2540025 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 3}2.765625 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1345431 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.1178078 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0135904{col 26}{space 2} .0118385{col 37}{space 1}    1.15{col 46}{space 3}0.251{col 54}{space 4}-.0096126{col 67}{space 3} .0367935
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0507068{col 26}{space 2} .0393292{col 37}{space 1}    1.29{col 46}{space 3}0.197{col 54}{space 4}-.0263769{col 67}{space 3} .1277906
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(stayathome))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-146.87893}  
Iteration 1:{space 3}log likelihood = {res:-122.04317}  
Iteration 2:{space 3}log likelihood = {res:-109.48266}  
Iteration 3:{space 3}log likelihood = {res:-106.41666}  
Iteration 4:{space 3}log likelihood = {res:-103.43457}  
Iteration 5:{space 3}log likelihood = {res:-101.92107}  
Iteration 6:{space 3}log likelihood = {res:-101.54171}  
Iteration 7:{space 3}log likelihood = {res:-101.53518}  
Iteration 8:{space 3}log likelihood = {res:-101.53517}  
Iteration 9:{space 3}log likelihood = {res:-101.53517}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,318
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     90.69
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-101.53517{txt}{col 49}Pseudo R2{col 67}= {res}    0.3087

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          gather{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2}  .762645{col 30}{space 2} .4371519{col 41}{space 1}    1.74{col 50}{space 3}0.081{col 58}{space 4}-.0941568{col 71}{space 3} 1.619447
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.2249726{col 30}{space 2} .3521483{col 41}{space 1}   -0.64{col 50}{space 3}0.523{col 58}{space 4}-.9151706{col 71}{space 3} .4652254
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0089786{col 30}{space 2} .0167585{col 41}{space 1}   -0.54{col 50}{space 3}0.592{col 58}{space 4}-.0418247{col 71}{space 3} .0238675
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0050373{col 30}{space 2}  .007805{col 41}{space 1}    0.65{col 50}{space 3}0.519{col 58}{space 4}-.0102603{col 71}{space 3}  .020335
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-8.918507{col 30}{space 2} 10.37199{col 41}{space 1}   -0.86{col 50}{space 3}0.390{col 58}{space 4}-29.24723{col 71}{space 3} 11.41022
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} -1.75484{col 30}{space 2} 1.101997{col 41}{space 1}   -1.59{col 50}{space 3}0.111{col 58}{space 4}-3.914715{col 71}{space 3} .4050342
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2835148{col 30}{space 2} .3395672{col 41}{space 1}   -0.83{col 50}{space 3}0.404{col 58}{space 4}-.9490544{col 71}{space 3} .3820248
{txt}{space 12}time {c |}{col 18}{res}{space 2} 2.545836{col 30}{space 2} 1.114331{col 41}{space 1}    2.28{col 50}{space 3}0.022{col 58}{space 4} .3617874{col 71}{space 3} 4.729885
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}  -.04986{col 30}{space 2} .0241017{col 41}{space 1}   -2.07{col 50}{space 3}0.039{col 58}{space 4}-.0970986{col 71}{space 3}-.0026215
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.6108414{col 30}{space 2}  .509901{col 41}{space 1}   -1.20{col 50}{space 3}0.231{col 58}{space 4}-1.610229{col 71}{space 3} .3885462
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2} -1.17362{col 30}{space 2} 2.272443{col 41}{space 1}   -0.52{col 50}{space 3}0.606{col 58}{space 4}-5.627526{col 71}{space 3} 3.280287
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} 2.008776{col 30}{space 2} 2.520115{col 41}{space 1}    0.80{col 50}{space 3}0.425{col 58}{space 4}-2.930559{col 71}{space 3} 6.948111
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-31.18901{col 30}{space 2} 13.07581{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4}-56.81712{col 71}{space 3}-5.560905
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 401 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}        21
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(gather), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 3}.6190476 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 3}.3809524 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 3}1.995238 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}15.10654 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}31.51681 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2159961 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.2688537 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 3}2.742857 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1318862 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.1233574 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0755499{col 26}{space 2} .0382954{col 37}{space 1}    1.97{col 46}{space 3}0.049{col 54}{space 4} .0004924{col 67}{space 3} .1506075
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .1490895{col 26}{space 2} .0709967{col 37}{space 1}    2.10{col 46}{space 3}0.036{col 54}{space 4} .0099385{col 67}{space 3} .2882405
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(gather))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-179.48635}  
Iteration 1:{space 3}log likelihood = {res:-149.16819}  
Iteration 2:{space 3}log likelihood = {res:-130.57723}  
Iteration 3:{space 3}log likelihood = {res: -121.3001}  
Iteration 4:{space 3}log likelihood = {res:-115.71292}  
Iteration 5:{space 3}log likelihood = {res: -114.8752}  
Iteration 6:{space 3}log likelihood = {res:-114.84823}  
Iteration 7:{space 3}log likelihood = {res:-114.84821}  
Iteration 8:{space 3}log likelihood = {res:-114.84821}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,130
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}    129.28
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-114.84821{txt}{col 49}Pseudo R2{col 67}= {res}    0.3601

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            bars{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2}-.0163802{col 30}{space 2}  .433757{col 41}{space 1}   -0.04{col 50}{space 3}0.970{col 58}{space 4}-.8665283{col 71}{space 3} .8337679
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.5675224{col 30}{space 2}  .340778{col 41}{space 1}   -1.67{col 50}{space 3}0.096{col 58}{space 4}-1.235435{col 71}{space 3} .1003902
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .2525843{col 30}{space 2}  .141186{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0241351{col 71}{space 3} .5293038
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0168325{col 30}{space 2} .0257317{col 41}{space 1}    0.65{col 50}{space 3}0.513{col 58}{space 4}-.0336007{col 71}{space 3} .0672657
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-9.486844{col 30}{space 2} 9.838358{col 41}{space 1}   -0.96{col 50}{space 3}0.335{col 58}{space 4}-28.76967{col 71}{space 3} 9.795983
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-1.441866{col 30}{space 2} .9327588{col 41}{space 1}   -1.55{col 50}{space 3}0.122{col 58}{space 4}-3.270039{col 71}{space 3}  .386308
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.5195631{col 30}{space 2} .3029684{col 41}{space 1}   -1.71{col 50}{space 3}0.086{col 58}{space 4} -1.11337{col 71}{space 3} .0742441
{txt}{space 12}time {c |}{col 18}{res}{space 2} 2.705477{col 30}{space 2} .5888732{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4} 1.551307{col 71}{space 3} 3.859647
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0652326{col 30}{space 2} .0149067{col 41}{space 1}   -4.38{col 50}{space 3}0.000{col 58}{space 4}-.0944493{col 71}{space 3}-.0360159
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.346422{col 30}{space 2}  .506649{col 41}{space 1}   -2.66{col 50}{space 3}0.008{col 58}{space 4}-2.339436{col 71}{space 3}-.3534083
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2}-.7322715{col 30}{space 2} 1.872636{col 41}{space 1}   -0.39{col 50}{space 3}0.696{col 58}{space 4} -4.40257{col 71}{space 3} 2.938027
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} -3.63021{col 30}{space 2} 2.321677{col 41}{space 1}   -1.56{col 50}{space 3}0.118{col 58}{space 4}-8.180612{col 71}{space 3} .9201923
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-24.21968{col 30}{space 2}  6.26593{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-36.50068{col 71}{space 3}-11.93868
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 266 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}         8
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(bars), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 7}.625 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 7}.375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 6}2.375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}7.477754 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}18.58482 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2108339 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.3054652 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 5}2.8375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1390947 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.1818874 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0313117{col 26}{space 2} .0244318{col 37}{space 1}    1.28{col 46}{space 3}0.200{col 54}{space 4}-.0165738{col 67}{space 3} .0791972
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0308187{col 26}{space 2} .0247271{col 37}{space 1}    1.25{col 46}{space 3}0.213{col 54}{space 4}-.0176455{col 67}{space 3} .0792829
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(bars))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-177.95483}  
Iteration 1:{space 3}log likelihood = {res:-139.50649}  
Iteration 2:{space 3}log likelihood = {res:-120.62638}  
Iteration 3:{space 3}log likelihood = {res:-113.79269}  
Iteration 4:{space 3}log likelihood = {res: -107.1049}  
Iteration 5:{space 3}log likelihood = {res:-106.47884}  
Iteration 6:{space 3}log likelihood = {res:-106.46036}  
Iteration 7:{space 3}log likelihood = {res:-106.46033}  
Iteration 8:{space 3}log likelihood = {res:-106.46033}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       946
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}    142.99
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-106.46033{txt}{col 49}Pseudo R2{col 67}= {res}    0.4018

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          school{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2} .2924221{col 30}{space 2}  .444957{col 41}{space 1}    0.66{col 50}{space 3}0.511{col 58}{space 4}-.5796777{col 71}{space 3} 1.164522
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.4066417{col 30}{space 2} .3175652{col 41}{space 1}   -1.28{col 50}{space 3}0.200{col 58}{space 4}-1.029058{col 71}{space 3} .2157747
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .2598099{col 30}{space 2} .2836392{col 41}{space 1}    0.92{col 50}{space 3}0.360{col 58}{space 4}-.2961127{col 71}{space 3} .8157325
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.1554637{col 30}{space 2} .1235727{col 41}{space 1}   -1.26{col 50}{space 3}0.208{col 58}{space 4}-.3976618{col 71}{space 3} .0867344
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-13.24222{col 30}{space 2} 10.27365{col 41}{space 1}   -1.29{col 50}{space 3}0.197{col 58}{space 4} -33.3782{col 71}{space 3} 6.893754
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-1.635272{col 30}{space 2} 1.101811{col 41}{space 1}   -1.48{col 50}{space 3}0.138{col 58}{space 4}-3.794782{col 71}{space 3}  .524237
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.7522722{col 30}{space 2}  .359435{col 41}{space 1}   -2.09{col 50}{space 3}0.036{col 58}{space 4}-1.456752{col 71}{space 3}-.0477925
{txt}{space 12}time {c |}{col 18}{res}{space 2} 3.571642{col 30}{space 2} .9485809{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} 1.712457{col 71}{space 3} 5.430826
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0940085{col 30}{space 2} .0280852{col 41}{space 1}   -3.35{col 50}{space 3}0.001{col 58}{space 4}-.1490545{col 71}{space 3}-.0389625
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} .0850941{col 30}{space 2} .3995636{col 41}{space 1}    0.21{col 50}{space 3}0.831{col 58}{space 4}-.6980362{col 71}{space 3} .8682245
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2} 3.061722{col 30}{space 2} 1.917057{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.6956397{col 71}{space 3} 6.819084
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2}-3.830583{col 30}{space 2} 2.416575{col 41}{space 1}   -1.59{col 50}{space 3}0.113{col 58}{space 4}-8.566982{col 71}{space 3} .9058157
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-28.43742{col 30}{space 2} 8.394802{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4}-44.89093{col 71}{space 3}-11.98391
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 297 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}         3
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(school), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 3}.6666667 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 3}.3333333 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 8}2.1 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}6.127522 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}19.44676 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2263058 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.2093698 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 3}2.966667 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.0599042 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 4}.083266 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2}   .00004{col 26}{space 2} .0001236{col 37}{space 1}    0.32{col 46}{space 3}0.746{col 54}{space 4}-.0002022{col 67}{space 3} .0002823
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0000536{col 26}{space 2} .0001654{col 37}{space 1}    0.32{col 46}{space 3}0.746{col 54}{space 4}-.0002705{col 67}{space 3} .0003777
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(school))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-144.91382}  
Iteration 1:{space 3}log likelihood = {res:-124.04852}  
Iteration 2:{space 3}log likelihood = {res: -111.5487}  
Iteration 3:{space 3}log likelihood = {res:-106.41093}  
Iteration 4:{space 3}log likelihood = {res:-105.26108}  
Iteration 5:{space 3}log likelihood = {res:-105.22283}  
Iteration 6:{space 3}log likelihood = {res:-105.22269}  
Iteration 7:{space 3}log likelihood = {res:-105.22269}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,238
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     79.38
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-105.22269{txt}{col 49}Pseudo R2{col 67}= {res}    0.2739

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              ui{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2} .3099668{col 30}{space 2} .4790534{col 41}{space 1}    0.65{col 50}{space 3}0.518{col 58}{space 4}-.6289606{col 71}{space 3} 1.248894
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.4892534{col 30}{space 2} .3205871{col 41}{space 1}   -1.53{col 50}{space 3}0.127{col 58}{space 4}-1.117593{col 71}{space 3} .1390858
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .0239648{col 30}{space 2} .0527683{col 41}{space 1}    0.45{col 50}{space 3}0.650{col 58}{space 4}-.0794592{col 71}{space 3} .1273889
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0493905{col 30}{space 2} .0397211{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-.1272423{col 71}{space 3} .0284613
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-3.096328{col 30}{space 2} 10.39595{col 41}{space 1}   -0.30{col 50}{space 3}0.766{col 58}{space 4}-23.47202{col 71}{space 3} 17.27936
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-1.016781{col 30}{space 2} 1.112468{col 41}{space 1}   -0.91{col 50}{space 3}0.361{col 58}{space 4}-3.197178{col 71}{space 3} 1.163616
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.1342831{col 30}{space 2} .3540729{col 41}{space 1}   -0.38{col 50}{space 3}0.705{col 58}{space 4}-.8282533{col 71}{space 3}  .559687
{txt}{space 12}time {c |}{col 18}{res}{space 2}  1.59508{col 30}{space 2} .5215433{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .5728742{col 71}{space 3} 2.617286
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0336821{col 30}{space 2} .0127019{col 41}{space 1}   -2.65{col 50}{space 3}0.008{col 58}{space 4}-.0585774{col 71}{space 3}-.0087868
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.638443{col 30}{space 2} .7434689{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-3.095616{col 71}{space 3}-.1812711
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2} .8145427{col 30}{space 2} 2.057542{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-3.218165{col 71}{space 3} 4.847251
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} 4.040273{col 30}{space 2} 2.254319{col 41}{space 1}    1.79{col 50}{space 3}0.073{col 58}{space 4}-.3781107{col 71}{space 3} 8.458657
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-18.98058{col 30}{space 2} 5.906253{col 41}{space 1}   -3.21{col 50}{space 3}0.001{col 58}{space 4}-30.55663{col 71}{space 3}-7.404539
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 154 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}        23
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(ui), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 3}.6521739 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 3}.3478261 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 3}2.130435 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}9.960998 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}36.80603 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2118361 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.2243623 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 3}2.626087 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1286567 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.1136706 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0176502{col 26}{space 2} .0186276{col 37}{space 1}    0.95{col 46}{space 3}0.343{col 54}{space 4}-.0188593{col 67}{space 3} .0541597
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0239106{col 26}{space 2} .0253885{col 37}{space 1}    0.94{col 46}{space 3}0.346{col 54}{space 4}  -.02585{col 67}{space 3} .0736712
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(ui))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.11011}  
Iteration 1:{space 3}log likelihood = {res:-86.555282}  
Iteration 2:{space 3}log likelihood = {res:-80.407732}  
Iteration 3:{space 3}log likelihood = {res:  -78.9477}  
Iteration 4:{space 3}log likelihood = {res:-78.439277}  
Iteration 5:{space 3}log likelihood = {res:-78.422842}  
Iteration 6:{space 3}log likelihood = {res:-78.422802}  
Iteration 7:{space 3}log likelihood = {res:-78.422802}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,367
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     43.37
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-78.422802{txt}{col 49}Pseudo R2{col 67}= {res}    0.2166

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       childcare{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2} .0725334{col 30}{space 2} .5337683{col 41}{space 1}    0.14{col 50}{space 3}0.892{col 58}{space 4}-.9736332{col 71}{space 3}   1.1187
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0501016{col 30}{space 2} .4020698{col 41}{space 1}   -0.12{col 50}{space 3}0.901{col 58}{space 4} -.838144{col 71}{space 3} .7379408
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0086537{col 30}{space 2} .0280335{col 41}{space 1}   -0.31{col 50}{space 3}0.758{col 58}{space 4}-.0635984{col 71}{space 3} .0462909
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0075108{col 30}{space 2} .0104681{col 41}{space 1}    0.72{col 50}{space 3}0.473{col 58}{space 4}-.0130063{col 71}{space 3} .0280279
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-17.41534{col 30}{space 2} 13.30021{col 41}{space 1}   -1.31{col 50}{space 3}0.190{col 58}{space 4}-43.48327{col 71}{space 3} 8.652582
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.5873898{col 30}{space 2} 1.295751{col 41}{space 1}   -0.45{col 50}{space 3}0.650{col 58}{space 4}-3.127014{col 71}{space 3} 1.952235
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2049597{col 30}{space 2} .4406579{col 41}{space 1}   -0.47{col 50}{space 3}0.642{col 58}{space 4}-1.068633{col 71}{space 3} .6587139
{txt}{space 12}time {c |}{col 18}{res}{space 2} .9956003{col 30}{space 2} .6056155{col 41}{space 1}    1.64{col 50}{space 3}0.100{col 58}{space 4}-.1913841{col 71}{space 3} 2.182585
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0191286{col 30}{space 2} .0139059{col 41}{space 1}   -1.38{col 50}{space 3}0.169{col 58}{space 4}-.0463836{col 71}{space 3} .0081264
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} -1.79081{col 30}{space 2}  1.04223{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-3.833543{col 71}{space 3} .2519231
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2}-1.867736{col 30}{space 2}  2.74208{col 41}{space 1}   -0.68{col 50}{space 3}0.496{col 58}{space 4}-7.242115{col 71}{space 3} 3.506643
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2}-.9037919{col 30}{space 2} 2.806745{col 41}{space 1}   -0.32{col 50}{space 3}0.747{col 58}{space 4}-6.404912{col 71}{space 3} 4.597328
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-10.92417{col 30}{space 2}  7.32236{col 41}{space 1}   -1.49{col 50}{space 3}0.136{col 58}{space 4}-25.27574{col 71}{space 3} 3.427389
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}        35
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(childcare), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 3}.5142857 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 3}.4857143 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 3}1.897143 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 3}13.58484 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}26.67497 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2161128 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.2418636 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 3}2.702857 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1233434 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.1188344 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0544775{col 26}{space 2} .0290464{col 37}{space 1}    1.88{col 46}{space 3}0.061{col 54}{space 4}-.0024523{col 67}{space 3} .1114074
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0583367{col 26}{space 2} .0305378{col 37}{space 1}    1.91{col 46}{space 3}0.056{col 54}{space 4}-.0015164{col 67}{space 3} .1181898
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(childcare))
(10 missing values generated)
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-91.185296}  
Iteration 1:{space 3}log likelihood = {res:-78.829422}  
Iteration 2:{space 3}log likelihood = {res:-70.114966}  
Iteration 3:{space 3}log likelihood = {res:-66.701647}  
Iteration 4:{space 3}log likelihood = {res:-65.194783}  
Iteration 5:{space 3}log likelihood = {res:-64.989174}  
Iteration 6:{space 3}log likelihood = {res:-64.987003}  
Iteration 7:{space 3}log likelihood = {res:-64.987003}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,344
{txt}{col 49}LR chi2({res}12{txt}){col 67}= {res}     52.40
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-64.987003{txt}{col 49}Pseudo R2{col 67}= {res}    0.2873

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        eviction{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}1.gov {c |}{col 18}{res}{space 2} .0556065{col 30}{space 2} .6378053{col 41}{space 1}    0.09{col 50}{space 3}0.931{col 58}{space 4}-1.194469{col 71}{space 3} 1.305682
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.4643181{col 30}{space 2} .4446134{col 41}{space 1}   -1.04{col 50}{space 3}0.296{col 58}{space 4}-1.335744{col 71}{space 3} .4071083
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0120425{col 30}{space 2} .0904546{col 41}{space 1}   -0.13{col 50}{space 3}0.894{col 58}{space 4}-.1893302{col 71}{space 3} .1652453
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0100703{col 30}{space 2} .0111993{col 41}{space 1}    0.90{col 50}{space 3}0.369{col 58}{space 4}  -.01188{col 71}{space 3} .0320205
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-13.63187{col 30}{space 2} 16.56367{col 41}{space 1}   -0.82{col 50}{space 3}0.411{col 58}{space 4}-46.09607{col 71}{space 3} 18.83233
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} 2.921268{col 30}{space 2} 1.363107{col 41}{space 1}    2.14{col 50}{space 3}0.032{col 58}{space 4} .2496274{col 71}{space 3} 5.592908
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .2334347{col 30}{space 2} .5412641{col 41}{space 1}    0.43{col 50}{space 3}0.666{col 58}{space 4}-.8274235{col 71}{space 3} 1.294293
{txt}{space 12}time {c |}{col 18}{res}{space 2}  2.43114{col 30}{space 2} 1.075454{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .3232899{col 71}{space 3} 4.538991
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0526073{col 30}{space 2} .0244027{col 41}{space 1}   -2.16{col 50}{space 3}0.031{col 58}{space 4}-.1004358{col 71}{space 3}-.0047788
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.832327{col 30}{space 2}  1.04691{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-3.884233{col 71}{space 3} .2195792
{txt}{space 7}black2018 {c |}{col 18}{res}{space 2}  .590943{col 30}{space 2} 3.098917{col 41}{space 1}    0.19{col 50}{space 3}0.849{col 58}{space 4}-5.482822{col 71}{space 3} 6.664708
{txt}{space 8}hisp2018 {c |}{col 18}{res}{space 2} 1.114044{col 30}{space 2} 3.834531{col 41}{space 1}    0.29{col 50}{space 3}0.771{col 58}{space 4}-6.401498{col 71}{space 3} 8.629587
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-28.65199{col 30}{space 2} 12.65701{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-53.45926{col 71}{space 3}-3.844709
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 330 failures and 0 successes completely determined.{p_end}
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}        32
{txt}{col 1}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(eviction), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:0.gov}{space 11}{txt:=} {space 6}.5625 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.gov}{space 11}{txt:=} {space 6}.4375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:stategdp}{space 8}{txt:=} {space 5}1.9125 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:per100k}{space 9}{txt:=} {space 4}9.58564 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:neighbor}{space 8}{txt:=} {space 3}29.06813 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:pop65}{space 11}{txt:=} {space 3}.2186729 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:popcon2016}{space 6}{txt:=} {space 3}.1840431 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hospita~2018}{space 4}{txt:=} {space 4}2.69375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:time}{space 12}{txt:=} {space 9}28 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:timesq}{space 10}{txt:=} {space 8}784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:weekend}{space 9}{txt:=} {space 10}0 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:black2018}{space 7}{txt:=} {space 3}.1258696 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:hisp2018}{space 8}{txt:=} {space 3}.0996906 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .0153089{col 26}{space 2} .0123613{col 37}{space 1}    1.24{col 46}{space 3}0.216{col 54}{space 4}-.0089189{col 67}{space 3} .0395367
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .0161701{col 26}{space 2} .0136947{col 37}{space 1}    1.18{col 46}{space 3}0.238{col 54}{space 4}-.0106711{col 67}{space 3} .0430113
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(option {bf:pr} assumed; Pr(eviction))
(10 missing values generated)

{com}. save $nfile, replace
{txt}file 204uoa_day20200330.dta saved

{com}. 
. 
. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX PREDICTED VALUE REPORTS XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX PREDICTED VALUE REPORTS XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
{txt}
{com}. foreach v of local vs {c -(}
{txt}  2{com}. drop _all
{txt}  3{com}. use $nfile
{txt}  4{com}. keep if date==326
{txt}  5{com}. keep state pred`v'
{txt}  6{com}. rename pred`v' pred
{txt}  7{com}. sort pred state
{txt}  8{com}. gen govaction="`v'"
{txt}  9{com}. append using temp
{txt} 10{com}. save temp, replace
{txt} 11{com}. {c )-}
{txt}(1,560 observations deleted)
{res}{txt}file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str8, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str10, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str6, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str4, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str6, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str2, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str9, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved
(1,560 observations deleted)
{res}{txt}{p 0 7 2}
(note: variable
govaction was 
str8, now str11 to accommodate using data's values)
{p_end}
file temp.dta saved

{com}. 
. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ROBUSTNESS TESTS XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ROBUSTNESS TESTS XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
{txt}
{com}. *DROP TIME TERM
. drop _all
{txt}
{com}. use $nfile
{txt}
{com}. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. logit `v' gov stategdp per100k neighbor pop65 popcon2016 hospitalbeds2018 weekend if date>226&date<327
{txt}  4{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-169.00668}  
Iteration 1:{space 3}log likelihood = {res: -166.1469}  
Iteration 2:{space 3}log likelihood = {res:-166.00349}  
Iteration 3:{space 3}log likelihood = {res:-166.00251}  
Iteration 4:{space 3}log likelihood = {res:-166.00251}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       776
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}      6.01
{txt}{col 49}Prob > chi2{col 67}= {res}    0.6463
{txt}Log likelihood = {res}-166.00251{txt}{col 49}Pseudo R2{col 67}= {res}    0.0178

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     soemergency{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0026996{col 30}{space 2}  .342547{col 41}{space 1}   -0.01{col 50}{space 3}0.994{col 58}{space 4}-.6740795{col 71}{space 3} .6686803
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0613833{col 30}{space 2} .2598877{col 41}{space 1}    0.24{col 50}{space 3}0.813{col 58}{space 4}-.4479872{col 71}{space 3} .5707538
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.1382699{col 30}{space 2} .2260063{col 41}{space 1}   -0.61{col 50}{space 3}0.541{col 58}{space 4}-.5812342{col 71}{space 3} .3046944
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0059999{col 30}{space 2} .0370191{col 41}{space 1}   -0.16{col 50}{space 3}0.871{col 58}{space 4} -.078556{col 71}{space 3} .0665562
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} .3894399{col 30}{space 2} 8.092574{col 41}{space 1}    0.05{col 50}{space 3}0.962{col 58}{space 4}-15.47171{col 71}{space 3} 16.25059
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.5109468{col 30}{space 2}  .833397{col 41}{space 1}   -0.61{col 50}{space 3}0.540{col 58}{space 4}-2.144375{col 71}{space 3} 1.122481
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.1927818{col 30}{space 2} .2687738{col 41}{space 1}   -0.72{col 50}{space 3}0.473{col 58}{space 4}-.7195688{col 71}{space 3} .3340052
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.7724307{col 30}{space 2}   .42074{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-1.597066{col 71}{space 3} .0522045
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-2.173047{col 30}{space 2} 2.258669{col 41}{space 1}   -0.96{col 50}{space 3}0.336{col 58}{space 4}-6.599957{col 71}{space 3} 2.253863
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-121.26385}  
Iteration 1:{space 3}log likelihood = {res:-118.47666}  
Iteration 2:{space 3}log likelihood = {res:-118.03339}  
Iteration 3:{space 3}log likelihood = {res:-118.03253}  
Iteration 4:{space 3}log likelihood = {res:-118.03253}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,188
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}      6.46
{txt}{col 49}Prob > chi2{col 67}= {res}    0.5956
{txt}Log likelihood = {res}-118.03253{txt}{col 49}Pseudo R2{col 67}= {res}    0.0266

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        natguard{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.3641253{col 30}{space 2} .4464187{col 41}{space 1}   -0.82{col 50}{space 3}0.415{col 58}{space 4} -1.23909{col 71}{space 3} .5108394
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0486457{col 30}{space 2} .3548978{col 41}{space 1}   -0.14{col 50}{space 3}0.891{col 58}{space 4}-.7442326{col 71}{space 3} .6469413
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .0517978{col 30}{space 2} .0683312{col 41}{space 1}    0.76{col 50}{space 3}0.448{col 58}{space 4}-.0821289{col 71}{space 3} .1857246
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0124617{col 30}{space 2} .0323044{col 41}{space 1}   -0.39{col 50}{space 3}0.700{col 58}{space 4}-.0757772{col 71}{space 3} .0508539
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-1.276043{col 30}{space 2}  11.2608{col 41}{space 1}   -0.11{col 50}{space 3}0.910{col 58}{space 4}-23.34681{col 71}{space 3} 20.79472
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} 1.438198{col 30}{space 2} .9282223{col 41}{space 1}    1.55{col 50}{space 3}0.121{col 58}{space 4} -.381084{col 71}{space 3} 3.257481
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.0456266{col 30}{space 2} .3624924{col 41}{space 1}   -0.13{col 50}{space 3}0.900{col 58}{space 4}-.7560986{col 71}{space 3} .6648454
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.7148241{col 30}{space 2} .5516629{col 41}{space 1}   -1.30{col 50}{space 3}0.195{col 58}{space 4}-1.796063{col 71}{space 3} .3664152
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-3.445247{col 30}{space 2} 3.113636{col 41}{space 1}   -1.11{col 50}{space 3}0.269{col 58}{space 4}-9.547861{col 71}{space 3} 2.657366
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.45684}  
Iteration 1:{space 3}log likelihood = {res:-98.086018}  
Iteration 2:{space 3}log likelihood = {res:-91.906978}  
Iteration 3:{space 3}log likelihood = {res:-91.770366}  
Iteration 4:{space 3}log likelihood = {res:-91.768538}  
Iteration 5:{space 3}log likelihood = {res:-91.768538}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,392
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     17.38
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0264
{txt}Log likelihood = {res}-91.768538{txt}{col 49}Pseudo R2{col 67}= {res}    0.0865

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      stayathome{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .9886698{col 30}{space 2} .5786369{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.1454378{col 71}{space 3} 2.122777
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.3467636{col 30}{space 2} .3923987{col 41}{space 1}   -0.88{col 50}{space 3}0.377{col 58}{space 4}-1.115851{col 71}{space 3} .4223237
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .0139745{col 30}{space 2} .0120827{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.0097071{col 71}{space 3} .0376562
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0202956{col 30}{space 2} .0073677{col 41}{space 1}    2.75{col 50}{space 3}0.006{col 58}{space 4} .0058552{col 71}{space 3}  .034736
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-6.304763{col 30}{space 2}  12.8421{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4}-31.47482{col 71}{space 3} 18.86529
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-2.360139{col 30}{space 2} 1.432898{col 41}{space 1}   -1.65{col 50}{space 3}0.100{col 58}{space 4}-5.168567{col 71}{space 3} .4482887
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.6335713{col 30}{space 2} .4423255{col 41}{space 1}   -1.43{col 50}{space 3}0.152{col 58}{space 4}-1.500513{col 71}{space 3} .2333707
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.2899828{col 30}{space 2} .5765984{col 41}{space 1}   -0.50{col 50}{space 3}0.615{col 58}{space 4}-1.420095{col 71}{space 3} .8401294
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.8558161{col 30}{space 2} 3.534402{col 41}{space 1}   -0.24{col 50}{space 3}0.809{col 58}{space 4}-7.783116{col 71}{space 3} 6.071484
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-146.87893}  
Iteration 1:{space 3}log likelihood = {res:-138.49833}  
Iteration 2:{space 3}log likelihood = {res:-137.28078}  
Iteration 3:{space 3}log likelihood = {res:-137.24998}  
Iteration 4:{space 3}log likelihood = {res:-137.24992}  
Iteration 5:{space 3}log likelihood = {res:-137.24992}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,318
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     19.26
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0135
{txt}Log likelihood = {res}-137.24992{txt}{col 49}Pseudo R2{col 67}= {res}    0.0656

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          gather{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}  .332555{col 30}{space 2} .4180742{col 41}{space 1}    0.80{col 50}{space 3}0.426{col 58}{space 4}-.4868554{col 71}{space 3} 1.151965
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.1055334{col 30}{space 2} .3153703{col 41}{space 1}   -0.33{col 50}{space 3}0.738{col 58}{space 4}-.7236478{col 71}{space 3}  .512581
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}  .011575{col 30}{space 2} .0110892{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4}-.0101594{col 71}{space 3} .0333094
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0248678{col 30}{space 2} .0064709{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0121851{col 71}{space 3} .0375504
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-7.345271{col 30}{space 2} 10.08197{col 41}{space 1}   -0.73{col 50}{space 3}0.466{col 58}{space 4}-27.10557{col 71}{space 3} 12.41502
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-1.356541{col 30}{space 2} 1.074327{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-3.462184{col 71}{space 3} .7491018
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2454054{col 30}{space 2} .3190107{col 41}{space 1}   -0.77{col 50}{space 3}0.442{col 58}{space 4}-.8706548{col 71}{space 3}  .379844
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.3979482{col 30}{space 2} .4657696{col 41}{space 1}   -0.85{col 50}{space 3}0.393{col 58}{space 4} -1.31084{col 71}{space 3} .5149434
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-1.267832{col 30}{space 2} 2.746728{col 41}{space 1}   -0.46{col 50}{space 3}0.644{col 58}{space 4} -6.65132{col 71}{space 3} 4.115655
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-179.48635}  
Iteration 1:{space 3}log likelihood = {res:-163.34662}  
Iteration 2:{space 3}log likelihood = {res:-158.42099}  
Iteration 3:{space 3}log likelihood = {res:-158.27458}  
Iteration 4:{space 3}log likelihood = {res:-158.27414}  
Iteration 5:{space 3}log likelihood = {res:-158.27414}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,130
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     42.42
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-158.27414{txt}{col 49}Pseudo R2{col 67}= {res}    0.1182

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            bars{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .0991453{col 30}{space 2}  .395005{col 41}{space 1}    0.25{col 50}{space 3}0.802{col 58}{space 4}-.6750502{col 71}{space 3} .8733408
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.5354551{col 30}{space 2} .2798297{col 41}{space 1}   -1.91{col 50}{space 3}0.056{col 58}{space 4}-1.083911{col 71}{space 3} .0130011
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .2919547{col 30}{space 2} .0835725{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .1281555{col 71}{space 3} .4557538
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0399793{col 30}{space 2} .0246084{col 41}{space 1}    1.62{col 50}{space 3}0.104{col 58}{space 4}-.0082522{col 71}{space 3} .0882108
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-6.900076{col 30}{space 2} 8.997318{col 41}{space 1}   -0.77{col 50}{space 3}0.443{col 58}{space 4} -24.5345{col 71}{space 3} 10.73434
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}  -1.9814{col 30}{space 2} .9240537{col 41}{space 1}   -2.14{col 50}{space 3}0.032{col 58}{space 4}-3.792512{col 71}{space 3}-.1702879
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2839228{col 30}{space 2} .2706114{col 41}{space 1}   -1.05{col 50}{space 3}0.294{col 58}{space 4}-.8143113{col 71}{space 3} .2464658
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.092046{col 30}{space 2} .4896992{col 41}{space 1}   -2.23{col 50}{space 3}0.026{col 58}{space 4}-2.051839{col 71}{space 3}-.1322533
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .2050713{col 30}{space 2} 2.504106{col 41}{space 1}    0.08{col 50}{space 3}0.935{col 58}{space 4}-4.702886{col 71}{space 3} 5.113029
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-177.95483}  
Iteration 1:{space 3}log likelihood = {res: -173.0604}  
Iteration 2:{space 3}log likelihood = {res:-172.30749}  
Iteration 3:{space 3}log likelihood = {res:-172.30327}  
Iteration 4:{space 3}log likelihood = {res:-172.30327}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       946
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     11.30
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1851
{txt}Log likelihood = {res}-172.30327{txt}{col 49}Pseudo R2{col 67}= {res}    0.0318

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          school{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0295825{col 30}{space 2} .3702569{col 41}{space 1}   -0.08{col 50}{space 3}0.936{col 58}{space 4}-.7552726{col 71}{space 3} .6961077
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} -.270021{col 30}{space 2} .2590041{col 41}{space 1}   -1.04{col 50}{space 3}0.297{col 58}{space 4}-.7776598{col 71}{space 3} .2376178
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .4787643{col 30}{space 2} .2147705{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4}  .057822{col 71}{space 3} .8997067
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0471715{col 30}{space 2} .0944152{col 41}{space 1}   -0.50{col 50}{space 3}0.617{col 58}{space 4} -.232222{col 71}{space 3} .1378789
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-9.753811{col 30}{space 2} 8.707274{col 41}{space 1}   -1.12{col 50}{space 3}0.263{col 58}{space 4}-26.81975{col 71}{space 3} 7.312132
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.3836251{col 30}{space 2} .8514261{col 41}{space 1}   -0.45{col 50}{space 3}0.652{col 58}{space 4} -2.05239{col 71}{space 3} 1.285139
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.0410794{col 30}{space 2} .2741474{col 41}{space 1}   -0.15{col 50}{space 3}0.881{col 58}{space 4}-.5783984{col 71}{space 3} .4962396
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} .3909088{col 30}{space 2} .3257689{col 41}{space 1}    1.20{col 50}{space 3}0.230{col 58}{space 4}-.2475864{col 71}{space 3} 1.029404
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.4540712{col 30}{space 2} 2.388183{col 41}{space 1}   -0.19{col 50}{space 3}0.849{col 58}{space 4}-5.134824{col 71}{space 3} 4.226681
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-144.91382}  
Iteration 1:{space 3}log likelihood = {res:  -138.976}  
Iteration 2:{space 3}log likelihood = {res:-135.86239}  
Iteration 3:{space 3}log likelihood = {res:-135.70058}  
Iteration 4:{space 3}log likelihood = {res:-135.69968}  
Iteration 5:{space 3}log likelihood = {res:-135.69968}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,238
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     18.43
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0182
{txt}Log likelihood = {res}-135.69968{txt}{col 49}Pseudo R2{col 67}= {res}    0.0636

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              ui{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0246813{col 30}{space 2} .4209666{col 41}{space 1}   -0.06{col 50}{space 3}0.953{col 58}{space 4}-.8497606{col 71}{space 3}  .800398
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.3694935{col 30}{space 2} .2980743{col 41}{space 1}   -1.24{col 50}{space 3}0.215{col 58}{space 4}-.9537084{col 71}{space 3} .2147213
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .1052952{col 30}{space 2} .0335704{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0394985{col 71}{space 3}  .171092
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0083764{col 30}{space 2} .0124085{col 41}{space 1}   -0.68{col 50}{space 3}0.500{col 58}{space 4}-.0326967{col 71}{space 3} .0159438
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-4.276292{col 30}{space 2} 10.08789{col 41}{space 1}   -0.42{col 50}{space 3}0.672{col 58}{space 4}-24.04819{col 71}{space 3}  15.4956
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.5196503{col 30}{space 2} .9977074{col 41}{space 1}   -0.52{col 50}{space 3}0.602{col 58}{space 4}-2.475121{col 71}{space 3}  1.43582
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} -.172828{col 30}{space 2} .3172253{col 41}{space 1}   -0.54{col 50}{space 3}0.586{col 58}{space 4}-.7945781{col 71}{space 3} .4489221
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.677646{col 30}{space 2} .7362015{col 41}{space 1}   -2.28{col 50}{space 3}0.023{col 58}{space 4}-3.120575{col 71}{space 3}-.2347176
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-1.341316{col 30}{space 2} 2.761122{col 41}{space 1}   -0.49{col 50}{space 3}0.627{col 58}{space 4}-6.753015{col 71}{space 3} 4.070384
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.11011}  
Iteration 1:{space 3}log likelihood = {res:-97.821256}  
Iteration 2:{space 3}log likelihood = {res:-93.098399}  
Iteration 3:{space 3}log likelihood = {res:-92.919269}  
Iteration 4:{space 3}log likelihood = {res:-92.917058}  
Iteration 5:{space 3}log likelihood = {res:-92.917057}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,367
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     14.39
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0722
{txt}Log likelihood = {res}-92.917057{txt}{col 49}Pseudo R2{col 67}= {res}    0.0719

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       childcare{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0131967{col 30}{space 2} .5165329{col 41}{space 1}   -0.03{col 50}{space 3}0.980{col 58}{space 4}-1.025583{col 71}{space 3} .9991891
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0784681{col 30}{space 2} .3837051{col 41}{space 1}   -0.20{col 50}{space 3}0.838{col 58}{space 4}-.8305162{col 71}{space 3}   .67358
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .0097079{col 30}{space 2} .0148547{col 41}{space 1}    0.65{col 50}{space 3}0.513{col 58}{space 4}-.0194067{col 71}{space 3} .0388224
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0204921{col 30}{space 2} .0082031{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0044143{col 71}{space 3}   .03657
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-19.06941{col 30}{space 2} 13.78824{col 41}{space 1}   -1.38{col 50}{space 3}0.167{col 58}{space 4}-46.09387{col 71}{space 3} 7.955047
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.9099985{col 30}{space 2} 1.267714{col 41}{space 1}   -0.72{col 50}{space 3}0.473{col 58}{space 4}-3.394672{col 71}{space 3} 1.574675
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.1145758{col 30}{space 2} .4278696{col 41}{space 1}   -0.27{col 50}{space 3}0.789{col 58}{space 4}-.9531849{col 71}{space 3} .7240332
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.846326{col 30}{space 2} 1.032623{col 41}{space 1}   -1.79{col 50}{space 3}0.074{col 58}{space 4}-3.870229{col 71}{space 3} .1775782
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .540975{col 30}{space 2} 3.552481{col 41}{space 1}    0.15{col 50}{space 3}0.879{col 58}{space 4}-6.421759{col 71}{space 3} 7.503709
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-91.185296}  
Iteration 1:{space 3}log likelihood = {res:   -85.823}  
Iteration 2:{space 3}log likelihood = {res:-80.471246}  
Iteration 3:{space 3}log likelihood = {res:-80.323309}  
Iteration 4:{space 3}log likelihood = {res:-80.321657}  
Iteration 5:{space 3}log likelihood = {res:-80.321656}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,344
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     21.73
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0054
{txt}Log likelihood = {res}-80.321656{txt}{col 49}Pseudo R2{col 67}= {res}    0.1191

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        eviction{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .0585991{col 30}{space 2} .5757524{col 41}{space 1}    0.10{col 50}{space 3}0.919{col 58}{space 4}-1.069855{col 71}{space 3} 1.187053
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.4626941{col 30}{space 2} .3928862{col 41}{space 1}   -1.18{col 50}{space 3}0.239{col 58}{space 4}-1.232737{col 71}{space 3} .3073488
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .0958387{col 30}{space 2} .0503546{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0028546{col 71}{space 3} .1945319
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0093245{col 30}{space 2} .0091668{col 41}{space 1}    1.02{col 50}{space 3}0.309{col 58}{space 4}-.0086422{col 71}{space 3} .0272911
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-12.37016{col 30}{space 2} 16.12084{col 41}{space 1}   -0.77{col 50}{space 3}0.443{col 58}{space 4}-43.96642{col 71}{space 3}  19.2261
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} 2.171406{col 30}{space 2} 1.198902{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.1783977{col 71}{space 3}  4.52121
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .2743663{col 30}{space 2} .4936923{col 41}{space 1}    0.56{col 50}{space 3}0.578{col 58}{space 4}-.6932529{col 71}{space 3} 1.241986
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.681715{col 30}{space 2} 1.039471{col 41}{space 1}   -1.62{col 50}{space 3}0.106{col 58}{space 4}-3.719041{col 71}{space 3} .3556112
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-2.327205{col 30}{space 2} 4.302453{col 41}{space 1}   -0.54{col 50}{space 3}0.589{col 58}{space 4}-10.75986{col 71}{space 3} 6.105448
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *NOTHING BUT GOVERNOR
. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. logit `v' gov if date>226&date<327
{txt}  4{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-169.00668}  
Iteration 1:{space 3}log likelihood = {res:-168.99328}  
Iteration 2:{space 3}log likelihood = {res:-168.99328}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       776
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.03
{txt}{col 49}Prob > chi2{col 67}= {res}    0.8700
{txt}Log likelihood = {res}-168.99328{txt}{col 49}Pseudo R2{col 67}= {res}    0.0001

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} soemergency{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2}-.0509855{col 26}{space 2} .3116966{col 37}{space 1}   -0.16{col 46}{space 3}0.870{col 54}{space 4}-.6618996{col 67}{space 3} .5599285
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.788093{col 26}{space 2} .2103111{col 37}{space 1}  -13.26{col 46}{space 3}0.000{col 54}{space 4}-3.200295{col 67}{space 3}-2.375891
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-121.26385}  
Iteration 1:{space 3}log likelihood = {res:-121.19579}  
Iteration 2:{space 3}log likelihood = {res: -121.1957}  
Iteration 3:{space 3}log likelihood = {res: -121.1957}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,188
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.14
{txt}{col 49}Prob > chi2{col 67}= {res}    0.7120
{txt}Log likelihood = {res} -121.1957{txt}{col 49}Pseudo R2{col 67}= {res}    0.0006

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    natguard{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2}-.1499553{col 26}{space 2} .4071661{col 37}{space 1}   -0.37{col 46}{space 3}0.713{col 54}{space 4}-.9479861{col 67}{space 3} .6480755
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.771118{col 26}{space 2} .2703208{col 37}{space 1}  -13.95{col 46}{space 3}0.000{col 54}{space 4}-4.300936{col 67}{space 3}-3.241299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.45684}  
Iteration 1:{space 3}log likelihood = {res:-97.785634}  
Iteration 2:{space 3}log likelihood = {res:-97.577048}  
Iteration 3:{space 3}log likelihood = {res: -97.57661}  
Iteration 4:{space 3}log likelihood = {res: -97.57661}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,392
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      5.76
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0164
{txt}Log likelihood = {res} -97.57661{txt}{col 49}Pseudo R2{col 67}= {res}    0.0287

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  stayathome{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2}  1.17408{col 26}{space 2} .5237911{col 37}{space 1}    2.24{col 46}{space 3}0.025{col 54}{space 4} .1474682{col 67}{space 3} 2.200692
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.991792{col 26}{space 2} .4487301{col 37}{space 1}  -11.12{col 46}{space 3}0.000{col 54}{space 4}-5.871287{col 67}{space 3}-4.112297
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-146.87893}  
Iteration 1:{space 3}log likelihood = {res:-146.09321}  
Iteration 2:{space 3}log likelihood = {res:-146.08362}  
Iteration 3:{space 3}log likelihood = {res:-146.08362}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,318
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      1.59
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2072
{txt}Log likelihood = {res}-146.08362{txt}{col 49}Pseudo R2{col 67}= {res}    0.0054

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      gather{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2}  .460827{col 26}{space 2} .3682403{col 37}{space 1}    1.25{col 46}{space 3}0.211{col 54}{space 4}-.2609106{col 67}{space 3} 1.182565
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.967385{col 26}{space 2} .2799619{col 37}{space 1}  -14.17{col 46}{space 3}0.000{col 54}{space 4}  -4.5161{col 67}{space 3} -3.41867
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-179.48635}  
Iteration 1:{space 3}log likelihood = {res:-179.40729}  
Iteration 2:{space 3}log likelihood = {res:-179.40722}  
Iteration 3:{space 3}log likelihood = {res:-179.40722}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,130
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.16
{txt}{col 49}Prob > chi2{col 67}= {res}    0.6908
{txt}Log likelihood = {res}-179.40722{txt}{col 49}Pseudo R2{col 67}= {res}    0.0004

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        bars{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2} .1251631{col 26}{space 2} .3145298{col 37}{space 1}    0.40{col 46}{space 3}0.691{col 54}{space 4}-.4913039{col 67}{space 3} .7416302
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.315051{col 26}{space 2} .2221467{col 37}{space 1}  -14.92{col 46}{space 3}0.000{col 54}{space 4}-3.750451{col 67}{space 3}-2.879652
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-177.95483}  
Iteration 1:{space 3}log likelihood = {res:-177.84236}  
Iteration 2:{space 3}log likelihood = {res:-177.84223}  
Iteration 3:{space 3}log likelihood = {res:-177.84223}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       946
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.23
{txt}{col 49}Prob > chi2{col 67}= {res}    0.6351
{txt}Log likelihood = {res}-177.84223{txt}{col 49}Pseudo R2{col 67}= {res}    0.0006

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      school{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2} .1466035{col 26}{space 2} .3088164{col 37}{space 1}    0.47{col 46}{space 3}0.635{col 54}{space 4}-.4586655{col 67}{space 3} .7518724
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.091042{col 26}{space 2} .2179923{col 37}{space 1}  -14.18{col 46}{space 3}0.000{col 54}{space 4}  -3.5183{col 67}{space 3}-2.663785
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-144.91382}  
Iteration 1:{space 3}log likelihood = {res:-144.73335}  
Iteration 2:{space 3}log likelihood = {res:-144.73285}  
Iteration 3:{space 3}log likelihood = {res:-144.73285}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,238
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.36
{txt}{col 49}Prob > chi2{col 67}= {res}    0.5474
{txt}Log likelihood = {res}-144.73285{txt}{col 49}Pseudo R2{col 67}= {res}    0.0012

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          ui{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2} .2189456{col 26}{space 2} .3640061{col 37}{space 1}    0.60{col 46}{space 3}0.548{col 54}{space 4}-.4944933{col 67}{space 3} .9323845
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.768922{col 26}{space 2} .2611611{col 37}{space 1}  -14.43{col 46}{space 3}0.000{col 54}{space 4}-4.280789{col 67}{space 3}-3.257056
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.11011}  
Iteration 1:{space 3}log likelihood = {res:-100.10969}  
Iteration 2:{space 3}log likelihood = {res:-100.10969}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,367
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.00
{txt}{col 49}Prob > chi2{col 67}= {res}    0.9771
{txt}Log likelihood = {res}-100.10969{txt}{col 49}Pseudo R2{col 67}= {res}    0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   childcare{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2}-.0133074{col 26}{space 2} .4626929{col 37}{space 1}   -0.03{col 46}{space 3}0.977{col 54}{space 4}-.9201689{col 67}{space 3} .8935541
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.255613{col 26}{space 2} .3184626{col 37}{space 1}  -13.36{col 46}{space 3}0.000{col 54}{space 4}-4.879788{col 67}{space 3}-3.631437
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-91.185296}  
Iteration 1:{space 3}log likelihood = {res:-90.716659}  
Iteration 2:{space 3}log likelihood = {res: -90.71021}  
Iteration 3:{space 3}log likelihood = {res:-90.710209}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,344
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      0.95
{txt}{col 49}Prob > chi2{col 67}= {res}    0.3297
{txt}Log likelihood = {res}-90.710209{txt}{col 49}Pseudo R2{col 67}= {res}    0.0052

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    eviction{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}gov {c |}{col 14}{res}{space 2} .4789068{col 26}{space 2} .4958656{col 37}{space 1}    0.97{col 46}{space 3}0.334{col 54}{space 4} -.492972{col 67}{space 3} 1.450786
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.610868{col 26}{space 2} .3798389{col 37}{space 1}  -12.14{col 46}{space 3}0.000{col 54}{space 4}-5.355339{col 67}{space 3}-3.866398
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *INTERACTION BTWN GOV PARTY & CASES PER 100K
. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. logit `v' gov stategdp per100k neighbor pop65 popcon2016 hospitalbeds2018 time timesq weekend inter if date>226&date<327
{txt}  4{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-169.00668}  
Iteration 1:{space 3}log likelihood = {res:-147.61286}  
Iteration 2:{space 3}log likelihood = {res:-138.55708}  
Iteration 3:{space 3}log likelihood = {res:-136.48869}  
Iteration 4:{space 3}log likelihood = {res:-135.71123}  
Iteration 5:{space 3}log likelihood = {res:-135.68391}  
Iteration 6:{space 3}log likelihood = {res:-135.68389}  
Iteration 7:{space 3}log likelihood = {res:-135.68389}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       776
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     66.65
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-135.68389{txt}{col 49}Pseudo R2{col 67}= {res}    0.1972

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     soemergency{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .6049664{col 30}{space 2} .4124004{col 41}{space 1}    1.47{col 50}{space 3}0.142{col 58}{space 4}-.2033234{col 71}{space 3} 1.413256
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0821335{col 30}{space 2} .2770057{col 41}{space 1}    0.30{col 50}{space 3}0.767{col 58}{space 4}-.4607876{col 71}{space 3} .6250547
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.8153082{col 30}{space 2} .8549215{col 41}{space 1}   -0.95{col 50}{space 3}0.340{col 58}{space 4}-2.490924{col 71}{space 3} .8603073
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .1061123{col 30}{space 2}  .212788{col 41}{space 1}    0.50{col 50}{space 3}0.618{col 58}{space 4}-.3109446{col 71}{space 3} .5231692
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-6.345107{col 30}{space 2} 8.829897{col 41}{space 1}   -0.72{col 50}{space 3}0.472{col 58}{space 4}-23.65139{col 71}{space 3} 10.96117
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.1270029{col 30}{space 2} .9326242{col 41}{space 1}   -0.14{col 50}{space 3}0.892{col 58}{space 4}-1.954913{col 71}{space 3} 1.700907
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2611996{col 30}{space 2} .3118866{col 41}{space 1}   -0.84{col 50}{space 3}0.402{col 58}{space 4}-.8724861{col 71}{space 3} .3500869
{txt}{space 12}time {c |}{col 18}{res}{space 2} .5823183{col 30}{space 2} .2155537{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .1598407{col 71}{space 3} 1.004796
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0128885{col 30}{space 2} .0098059{col 41}{space 1}   -1.31{col 50}{space 3}0.189{col 58}{space 4}-.0321077{col 71}{space 3} .0063307
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.5994218{col 30}{space 2}   .43556{col 41}{space 1}   -1.38{col 50}{space 3}0.169{col 58}{space 4}-1.453104{col 71}{space 3}   .25426
{txt}{space 11}inter {c |}{col 18}{res}{space 2}-3.492325{col 30}{space 2} 2.056155{col 41}{space 1}   -1.70{col 50}{space 3}0.089{col 58}{space 4}-7.522315{col 71}{space 3}  .537664
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-5.188989{col 30}{space 2} 2.603723{col 41}{space 1}   -1.99{col 50}{space 3}0.046{col 58}{space 4}-10.29219{col 71}{space 3} -.085786
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 15 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-121.26385}  
Iteration 1:{space 3}log likelihood = {res:-110.22238}  
Iteration 2:{space 3}log likelihood = {res:-104.57182}  
Iteration 3:{space 3}log likelihood = {res:-104.02755}  
Iteration 4:{space 3}log likelihood = {res:-104.01725}  
Iteration 5:{space 3}log likelihood = {res:-104.01724}  
Iteration 6:{space 3}log likelihood = {res:-104.01724}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,188
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     34.49
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0003
{txt}Log likelihood = {res}-104.01724{txt}{col 49}Pseudo R2{col 67}= {res}    0.1422

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        natguard{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.1562834{col 30}{space 2} .5427583{col 41}{space 1}   -0.29{col 50}{space 3}0.773{col 58}{space 4} -1.22007{col 71}{space 3} .9075034
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0007763{col 30}{space 2} .3982267{col 41}{space 1}    0.00{col 50}{space 3}0.998{col 58}{space 4}-.7797336{col 71}{space 3} .7812863
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .1481029{col 30}{space 2} .2616468{col 41}{space 1}    0.57{col 50}{space 3}0.571{col 58}{space 4}-.3647153{col 71}{space 3} .6609212
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0950079{col 30}{space 2} .0970994{col 41}{space 1}   -0.98{col 50}{space 3}0.328{col 58}{space 4}-.2853192{col 71}{space 3} .0953034
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 2.322337{col 30}{space 2} 11.56958{col 41}{space 1}    0.20{col 50}{space 3}0.841{col 58}{space 4}-20.35363{col 71}{space 3} 24.99831
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} 1.649422{col 30}{space 2} .9793328{col 41}{space 1}    1.68{col 50}{space 3}0.092{col 58}{space 4}-.2700353{col 71}{space 3} 3.568879
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.1006307{col 30}{space 2} .3636579{col 41}{space 1}   -0.28{col 50}{space 3}0.782{col 58}{space 4}-.8133872{col 71}{space 3} .6121258
{txt}{space 12}time {c |}{col 18}{res}{space 2} .7054362{col 30}{space 2} .2840698{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .1486696{col 71}{space 3} 1.262203
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0172955{col 30}{space 2} .0091888{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.0353051{col 71}{space 3} .0007142
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.7152507{col 30}{space 2} .5557841{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-1.804568{col 71}{space 3} .3740661
{txt}{space 11}inter {c |}{col 18}{res}{space 2}-.2438021{col 30}{space 2} .2735393{col 41}{space 1}   -0.89{col 50}{space 3}0.373{col 58}{space 4}-.7799293{col 71}{space 3} .2923252
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-10.24875{col 30}{space 2} 3.852192{col 41}{space 1}   -2.66{col 50}{space 3}0.008{col 58}{space 4} -17.7989{col 71}{space 3}-2.698588
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 1 failure and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.45684}  
Iteration 1:{space 3}log likelihood = {res: -81.94893}  
Iteration 2:{space 3}log likelihood = {res:-69.657084}  
Iteration 3:{space 3}log likelihood = {res:-68.206333}  
Iteration 4:{space 3}log likelihood = {res:-66.171081}  
Iteration 5:{space 3}log likelihood = {res:-64.075608}  
Iteration 6:{space 3}log likelihood = {res:-62.028911}  
Iteration 7:{space 3}log likelihood = {res:   -61.887}  
Iteration 8:{space 3}log likelihood = {res:-61.886006}  
Iteration 9:{space 3}log likelihood = {res:-61.886006}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,392
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     77.14
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-61.886006{txt}{col 49}Pseudo R2{col 67}= {res}    0.3840

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      stayathome{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} 1.250853{col 30}{space 2} .9724816{col 41}{space 1}    1.29{col 50}{space 3}0.198{col 58}{space 4}-.6551757{col 71}{space 3} 3.156882
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.5713884{col 30}{space 2} .4339059{col 41}{space 1}   -1.32{col 50}{space 3}0.188{col 58}{space 4}-1.421828{col 71}{space 3} .2790515
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0258669{col 30}{space 2} .1817238{col 41}{space 1}   -0.14{col 50}{space 3}0.887{col 58}{space 4}-.3820391{col 71}{space 3} .3303052
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0015255{col 30}{space 2} .0107199{col 41}{space 1}   -0.14{col 50}{space 3}0.887{col 58}{space 4}-.0225362{col 71}{space 3} .0194851
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-5.814407{col 30}{space 2} 13.53937{col 41}{space 1}   -0.43{col 50}{space 3}0.668{col 58}{space 4}-32.35109{col 71}{space 3} 20.72227
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-2.002485{col 30}{space 2} 1.361173{col 41}{space 1}   -1.47{col 50}{space 3}0.141{col 58}{space 4}-4.670335{col 71}{space 3} .6653655
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.8442078{col 30}{space 2}  .486144{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-1.797033{col 71}{space 3}  .108617
{txt}{space 12}time {c |}{col 18}{res}{space 2} 8.291799{col 30}{space 2} 3.262236{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} 1.897934{col 71}{space 3} 14.68566
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.1637589{col 30}{space 2} .0669246{col 41}{space 1}   -2.45{col 50}{space 3}0.014{col 58}{space 4}-.2949287{col 71}{space 3}-.0325891
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}   -.8766{col 30}{space 2} .6847958{col 41}{space 1}   -1.28{col 50}{space 3}0.201{col 58}{space 4}-2.218775{col 71}{space 3} .4655752
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .0169841{col 30}{space 2} .1811523{col 41}{space 1}    0.09{col 50}{space 3}0.925{col 58}{space 4}-.3380679{col 71}{space 3} .3720362
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-102.5087{col 30}{space 2} 39.63279{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-180.1875{col 71}{space 3}-24.82986
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 804 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-146.87893}  
Iteration 1:{space 3}log likelihood = {res:-122.26062}  
Iteration 2:{space 3}log likelihood = {res:-110.26412}  
Iteration 3:{space 3}log likelihood = {res:-106.72719}  
Iteration 4:{space 3}log likelihood = {res: -103.7029}  
Iteration 5:{space 3}log likelihood = {res:-102.20074}  
Iteration 6:{space 3}log likelihood = {res:-101.86252}  
Iteration 7:{space 3}log likelihood = {res: -101.8577}  
Iteration 8:{space 3}log likelihood = {res: -101.8577}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,318
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     90.04
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -101.8577{txt}{col 49}Pseudo R2{col 67}= {res}    0.3065

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          gather{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} 1.007221{col 30}{space 2} .6021881{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.1730461{col 71}{space 3} 2.187488
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.1538625{col 30}{space 2} .3375581{col 41}{space 1}   -0.46{col 50}{space 3}0.649{col 58}{space 4}-.8154643{col 71}{space 3} .5077393
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .0620828{col 30}{space 2} .1221914{col 41}{space 1}    0.51{col 50}{space 3}0.611{col 58}{space 4} -.177408{col 71}{space 3} .3015735
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0044908{col 30}{space 2} .0078361{col 41}{space 1}    0.57{col 50}{space 3}0.567{col 58}{space 4}-.0108676{col 71}{space 3} .0198492
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-8.644295{col 30}{space 2} 10.41625{col 41}{space 1}   -0.83{col 50}{space 3}0.407{col 58}{space 4}-29.05976{col 71}{space 3} 11.77117
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} -1.63953{col 30}{space 2} 1.072099{col 41}{space 1}   -1.53{col 50}{space 3}0.126{col 58}{space 4}-3.740806{col 71}{space 3} .4617464
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.3539648{col 30}{space 2} .3275012{col 41}{space 1}   -1.08{col 50}{space 3}0.280{col 58}{space 4}-.9958553{col 71}{space 3} .2879258
{txt}{space 12}time {c |}{col 18}{res}{space 2} 2.548775{col 30}{space 2}  1.10529{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .3824463{col 71}{space 3} 4.715104
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0505294{col 30}{space 2} .0240755{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.0977166{col 71}{space 3}-.0033423
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.6245799{col 30}{space 2} .5090502{col 41}{space 1}   -1.23{col 50}{space 3}0.220{col 58}{space 4}  -1.6223{col 71}{space 3} .3731403
{txt}{space 11}inter {c |}{col 18}{res}{space 2}-.0698973{col 30}{space 2} .1213305{col 41}{space 1}   -0.58{col 50}{space 3}0.565{col 58}{space 4}-.3077007{col 71}{space 3}  .167906
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} -31.0564{col 30}{space 2} 12.88234{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-56.30532{col 71}{space 3}-5.807487
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 393 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-179.48635}  
Iteration 1:{space 3}log likelihood = {res:-150.12972}  
Iteration 2:{space 3}log likelihood = {res: -131.7854}  
Iteration 3:{space 3}log likelihood = {res:-122.18643}  
Iteration 4:{space 3}log likelihood = {res:-116.93323}  
Iteration 5:{space 3}log likelihood = {res:-116.26099}  
Iteration 6:{space 3}log likelihood = {res:-116.24542}  
Iteration 7:{space 3}log likelihood = {res:-116.24542}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,130
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}    126.48
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-116.24542{txt}{col 49}Pseudo R2{col 67}= {res}    0.3523

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            bars{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0825663{col 30}{space 2} .5001649{col 41}{space 1}   -0.17{col 50}{space 3}0.869{col 58}{space 4}-1.062872{col 71}{space 3}  .897739
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.7078557{col 30}{space 2} .3257101{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-1.346236{col 71}{space 3}-.0694756
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .2184482{col 30}{space 2} .1722226{col 41}{space 1}    1.27{col 50}{space 3}0.205{col 58}{space 4}-.1191018{col 71}{space 3} .5559983
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0232732{col 30}{space 2} .0271093{col 41}{space 1}    0.86{col 50}{space 3}0.391{col 58}{space 4}  -.02986{col 71}{space 3} .0764064
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-8.003816{col 30}{space 2} 9.776322{col 41}{space 1}   -0.82{col 50}{space 3}0.413{col 58}{space 4}-27.16506{col 71}{space 3} 11.15742
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-1.534276{col 30}{space 2} .9400663{col 41}{space 1}   -1.63{col 50}{space 3}0.103{col 58}{space 4}-3.376772{col 71}{space 3} .3082199
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.3576357{col 30}{space 2} .2886538{col 41}{space 1}   -1.24{col 50}{space 3}0.215{col 58}{space 4}-.9233868{col 71}{space 3} .2081153
{txt}{space 12}time {c |}{col 18}{res}{space 2} 2.651266{col 30}{space 2} .5818696{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} 1.510822{col 71}{space 3} 3.791709
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0638311{col 30}{space 2} .0147516{col 41}{space 1}   -4.33{col 50}{space 3}0.000{col 58}{space 4}-.0927436{col 71}{space 3}-.0349185
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.294312{col 30}{space 2} .5039039{col 41}{space 1}   -2.57{col 50}{space 3}0.010{col 58}{space 4}-2.281945{col 71}{space 3}-.3066784
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .0136133{col 30}{space 2}  .160474{col 41}{space 1}    0.08{col 50}{space 3}0.932{col 58}{space 4}-.3009099{col 71}{space 3} .3281366
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-24.66283{col 30}{space 2} 6.227995{col 41}{space 1}   -3.96{col 50}{space 3}0.000{col 58}{space 4}-36.86948{col 71}{space 3}-12.45619
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 257 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-177.95483}  
Iteration 1:{space 3}log likelihood = {res: -140.1187}  
Iteration 2:{space 3}log likelihood = {res:-122.43302}  
Iteration 3:{space 3}log likelihood = {res:-116.05528}  
Iteration 4:{space 3}log likelihood = {res:-109.44439}  
Iteration 5:{space 3}log likelihood = {res:-108.76384}  
Iteration 6:{space 3}log likelihood = {res:-108.74483}  
Iteration 7:{space 3}log likelihood = {res:-108.74477}  
Iteration 8:{space 3}log likelihood = {res:-108.74477}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       946
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}    138.42
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-108.74477{txt}{col 49}Pseudo R2{col 67}= {res}    0.3889

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          school{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .3966366{col 30}{space 2}  .536936{col 41}{space 1}    0.74{col 50}{space 3}0.460{col 58}{space 4}-.6557386{col 71}{space 3} 1.449012
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} -.486552{col 30}{space 2} .3101345{col 41}{space 1}   -1.57{col 50}{space 3}0.117{col 58}{space 4}-1.094404{col 71}{space 3} .1213005
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .8524506{col 30}{space 2} .6478454{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}-.4173031{col 71}{space 3} 2.122204
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.1637593{col 30}{space 2} .1222184{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-.4033028{col 71}{space 3} .0757843
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-9.920674{col 30}{space 2} 9.481774{col 41}{space 1}   -1.05{col 50}{space 3}0.295{col 58}{space 4}-28.50461{col 71}{space 3} 8.663261
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-1.756519{col 30}{space 2} 1.134601{col 41}{space 1}   -1.55{col 50}{space 3}0.122{col 58}{space 4}-3.980297{col 71}{space 3} .4672577
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.5131118{col 30}{space 2} .3214896{col 41}{space 1}   -1.60{col 50}{space 3}0.110{col 58}{space 4} -1.14322{col 71}{space 3} .1169963
{txt}{space 12}time {c |}{col 18}{res}{space 2} 3.517027{col 30}{space 2} .9138521{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4}  1.72591{col 71}{space 3} 5.308144
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} -.093822{col 30}{space 2} .0270421{col 41}{space 1}   -3.47{col 50}{space 3}0.001{col 58}{space 4}-.1468235{col 71}{space 3}-.0408206
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0079783{col 30}{space 2} .3928154{col 41}{space 1}   -0.02{col 50}{space 3}0.984{col 58}{space 4}-.7778822{col 71}{space 3} .7619257
{txt}{space 11}inter {c |}{col 18}{res}{space 2} -.644129{col 30}{space 2}  .638356{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-1.895284{col 71}{space 3} .6070258
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} -28.9698{col 30}{space 2}  8.09273{col 41}{space 1}   -3.58{col 50}{space 3}0.000{col 58}{space 4}-44.83126{col 71}{space 3}-13.10834
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 287 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-144.91382}  
Iteration 1:{space 3}log likelihood = {res: -124.7676}  
Iteration 2:{space 3}log likelihood = {res:-112.68283}  
Iteration 3:{space 3}log likelihood = {res:-107.46075}  
Iteration 4:{space 3}log likelihood = {res:-106.11264}  
Iteration 5:{space 3}log likelihood = {res:-106.06759}  
Iteration 6:{space 3}log likelihood = {res:-106.06744}  
Iteration 7:{space 3}log likelihood = {res:-106.06744}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,238
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     77.69
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-106.06744{txt}{col 49}Pseudo R2{col 67}= {res}    0.2681

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              ui{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .6286584{col 30}{space 2} .5305347{col 41}{space 1}    1.18{col 50}{space 3}0.236{col 58}{space 4}-.4111706{col 71}{space 3} 1.668487
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} -.338621{col 30}{space 2} .3152288{col 41}{space 1}   -1.07{col 50}{space 3}0.283{col 58}{space 4}-.9564582{col 71}{space 3} .2792162
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .1808952{col 30}{space 2} .1467003{col 41}{space 1}    1.23{col 50}{space 3}0.218{col 58}{space 4}-.1066321{col 71}{space 3} .4684226
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0462045{col 30}{space 2}  .035885{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-.1165377{col 71}{space 3} .0241288
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-2.544962{col 30}{space 2} 10.38263{col 41}{space 1}   -0.25{col 50}{space 3}0.806{col 58}{space 4}-22.89455{col 71}{space 3} 17.80463
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.6744738{col 30}{space 2} 1.079706{col 41}{space 1}   -0.62{col 50}{space 3}0.532{col 58}{space 4}-2.790658{col 71}{space 3}  1.44171
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.2583175{col 30}{space 2} .3327854{col 41}{space 1}   -0.78{col 50}{space 3}0.438{col 58}{space 4}-.9105649{col 71}{space 3} .3939299
{txt}{space 12}time {c |}{col 18}{res}{space 2}  1.77961{col 30}{space 2}  .560644{col 41}{space 1}    3.17{col 50}{space 3}0.002{col 58}{space 4} .6807677{col 71}{space 3} 2.878452
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0394789{col 30}{space 2}  .013906{col 41}{space 1}   -2.84{col 50}{space 3}0.005{col 58}{space 4}-.0667341{col 71}{space 3}-.0122236
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.650988{col 30}{space 2} .7426948{col 41}{space 1}   -2.22{col 50}{space 3}0.026{col 58}{space 4}-3.106643{col 71}{space 3}-.1953327
{txt}{space 11}inter {c |}{col 18}{res}{space 2}-.1593072{col 30}{space 2}  .133851{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.4216504{col 71}{space 3} .1030361
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-20.12054{col 30}{space 2} 6.254185{col 41}{space 1}   -3.22{col 50}{space 3}0.001{col 58}{space 4}-32.37852{col 71}{space 3}-7.862565
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 191 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.11011}  
Iteration 1:{space 3}log likelihood = {res:-86.691563}  
Iteration 2:{space 3}log likelihood = {res:-80.589269}  
Iteration 3:{space 3}log likelihood = {res:-79.172229}  
Iteration 4:{space 3}log likelihood = {res:-78.705376}  
Iteration 5:{space 3}log likelihood = {res: -78.69076}  
Iteration 6:{space 3}log likelihood = {res:-78.690727}  
Iteration 7:{space 3}log likelihood = {res:-78.690727}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,367
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     42.84
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-78.690727{txt}{col 49}Pseudo R2{col 67}= {res}    0.2140

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       childcare{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0319702{col 30}{space 2} .6647303{col 41}{space 1}   -0.05{col 50}{space 3}0.962{col 58}{space 4}-1.334818{col 71}{space 3} 1.270877
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0539675{col 30}{space 2} .3778845{col 41}{space 1}   -0.14{col 50}{space 3}0.886{col 58}{space 4}-.7946075{col 71}{space 3} .6866724
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0337385{col 30}{space 2} .1104349{col 41}{space 1}   -0.31{col 50}{space 3}0.760{col 58}{space 4}-.2501869{col 71}{space 3} .1827099
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0078474{col 30}{space 2} .0111953{col 41}{space 1}    0.70{col 50}{space 3}0.483{col 58}{space 4}-.0140949{col 71}{space 3} .0297898
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-16.64465{col 30}{space 2} 13.38234{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-42.87354{col 71}{space 3} 9.584253
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.6131459{col 30}{space 2} 1.327303{col 41}{space 1}   -0.46{col 50}{space 3}0.644{col 58}{space 4}-3.214611{col 71}{space 3}  1.98832
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.1895936{col 30}{space 2} .4320906{col 41}{space 1}   -0.44{col 50}{space 3}0.661{col 58}{space 4}-1.036476{col 71}{space 3} .6572885
{txt}{space 12}time {c |}{col 18}{res}{space 2} .9682435{col 30}{space 2} .6052473{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.2180194{col 71}{space 3} 2.154506
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0183078{col 30}{space 2} .0139777{col 41}{space 1}   -1.31{col 50}{space 3}0.190{col 58}{space 4}-.0457036{col 71}{space 3}  .009088
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.787848{col 30}{space 2} 1.041941{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-3.830015{col 71}{space 3} .2543185
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .0236692{col 30}{space 2} .1077281{col 41}{space 1}    0.22{col 50}{space 3}0.826{col 58}{space 4}-.1874741{col 71}{space 3} .2348124
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} -11.1733{col 30}{space 2} 7.292636{col 41}{space 1}   -1.53{col 50}{space 3}0.125{col 58}{space 4}-25.46661{col 71}{space 3}     3.12
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-91.185296}  
Iteration 1:{space 3}log likelihood = {res:-79.276953}  
Iteration 2:{space 3}log likelihood = {res: -70.33984}  
Iteration 3:{space 3}log likelihood = {res: -67.26798}  
Iteration 4:{space 3}log likelihood = {res:-65.383185}  
Iteration 5:{space 3}log likelihood = {res:-65.044822}  
Iteration 6:{space 3}log likelihood = {res: -65.04047}  
Iteration 7:{space 3}log likelihood = {res:-65.040467}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,344
{txt}{col 49}LR chi2({res}11{txt}){col 67}= {res}     52.29
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-65.040467{txt}{col 49}Pseudo R2{col 67}= {res}    0.2867

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        eviction{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .0652645{col 30}{space 2} .8164321{col 41}{space 1}    0.08{col 50}{space 3}0.936{col 58}{space 4}-1.534913{col 71}{space 3} 1.665442
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.4550283{col 30}{space 2} .4178168{col 41}{space 1}   -1.09{col 50}{space 3}0.276{col 58}{space 4}-1.273934{col 71}{space 3} .3638776
{txt}{space 9}per100k {c |}{col 18}{res}{space 2}-.0158068{col 30}{space 2}  .150365{col 41}{space 1}   -0.11{col 50}{space 3}0.916{col 58}{space 4}-.3105168{col 71}{space 3} .2789032
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0098308{col 30}{space 2} .0115616{col 41}{space 1}    0.85{col 50}{space 3}0.395{col 58}{space 4}-.0128296{col 71}{space 3} .0324912
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-13.97496{col 30}{space 2} 16.03759{col 41}{space 1}   -0.87{col 50}{space 3}0.384{col 58}{space 4}-45.40806{col 71}{space 3} 17.45813
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} 3.000695{col 30}{space 2} 1.355042{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4}  .344862{col 71}{space 3} 5.656528
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .1892014{col 30}{space 2}  .515726{col 41}{space 1}    0.37{col 50}{space 3}0.714{col 58}{space 4}-.8216029{col 71}{space 3} 1.200006
{txt}{space 12}time {c |}{col 18}{res}{space 2}  2.42154{col 30}{space 2} 1.073003{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .3184928{col 71}{space 3} 4.524587
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0523516{col 30}{space 2} .0243522{col 41}{space 1}   -2.15{col 50}{space 3}0.032{col 58}{space 4} -.100081{col 71}{space 3}-.0046222
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-1.833283{col 30}{space 2} 1.046822{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-3.885015{col 71}{space 3}   .21845
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .0043885{col 30}{space 2} .1348493{col 41}{space 1}    0.03{col 50}{space 3}0.974{col 58}{space 4}-.2599112{col 71}{space 3} .2686883
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-28.20302{col 30}{space 2} 12.50049{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-52.70353{col 71}{space 3}-3.702517
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 328 failures and 0 successes completely determined.{p_end}

{com}. 
. *MULTICOLLINEARITY ANALYSIS, INCLUDING INTERACTION
. *Don't report time and timesq, as they're going to be highly collinear with each other.
. local xs gov stategdp per100k neighbor pop65 popcon2016 hospitalbeds2018 time timesq weekend inter
{txt}
{com}. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. foreach x of local xs {c -(}
{txt}  4{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS `x' XXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  5{com}. local otherxs: list xs - x
{txt}  6{com}. quietly reg `x' `otherxs' if `v'!=.&date>226&date<327
{txt}  7{com}. local r2=e(r2)
{txt}  8{com}. if `r2'>.8&"`x'"!="time"&"`x'"!="timesq" reg `x' `otherxs' if `v'!=.&date>226&date<327
{txt}  9{com}. {c )-}
{txt} 10{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       776
{txt}{hline 13}{c +}{hline 34}   F(10, 765)      = {res}  1067.95
{txt}       Model {c |} {res}  1444.5559        10   144.45559   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 103.477362       765  .135264525   {txt}R-squared       ={res}    0.9332
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9323
{txt}       Total {c |} {res} 1548.03326       775  1.99746227   {txt}Root MSE        =   {res} .36778

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.1218947{col 30}{space 2} .0297644{col 41}{space 1}   -4.10{col 50}{space 3}0.000{col 58}{space 4}-.1803244{col 71}{space 3} -.063465
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0102055{col 30}{space 2} .0221774{col 41}{space 1}    0.46{col 50}{space 3}0.646{col 58}{space 4}-.0333303{col 71}{space 3} .0537414
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0087007{col 30}{space 2} .0017338{col 41}{space 1}   -5.02{col 50}{space 3}0.000{col 58}{space 4}-.0121042{col 71}{space 3}-.0052972
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 1.775957{col 30}{space 2} .7091526{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .3838408{col 71}{space 3} 3.168073
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}  .016066{col 30}{space 2} .0690616{col 41}{space 1}    0.23{col 50}{space 3}0.816{col 58}{space 4}-.1195068{col 71}{space 3} .1516388
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} -.054892{col 30}{space 2} .0230798{col 41}{space 1}   -2.38{col 50}{space 3}0.018{col 58}{space 4}-.1001993{col 71}{space 3}-.0095848
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1175471{col 30}{space 2} .0066239{col 41}{space 1}  -17.75{col 50}{space 3}0.000{col 58}{space 4}-.1305503{col 71}{space 3}-.1045439
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0082461{col 30}{space 2} .0003124{col 41}{space 1}   26.40{col 50}{space 3}0.000{col 58}{space 4} .0076328{col 71}{space 3} .0088594
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} -.023442{col 30}{space 2} .0295002{col 41}{space 1}   -0.79{col 50}{space 3}0.427{col 58}{space 4}-.0813529{col 71}{space 3} .0344689
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .6890057{col 30}{space 2} .0152961{col 41}{space 1}   45.04{col 50}{space 3}0.000{col 58}{space 4} .6589783{col 71}{space 3}  .719033
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .058248{col 30}{space 2} .1976709{col 41}{space 1}    0.29{col 50}{space 3}0.768{col 58}{space 4}-.3297939{col 71}{space 3} .4462899
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       776
{txt}{hline 13}{c +}{hline 34}   F(10, 765)      = {res}   564.89
{txt}       Model {c |} {res} 1168.84069        10  116.884069   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 158.290777       765  .206916049   {txt}R-squared       ={res}    0.8807
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8792
{txt}       Total {c |} {res} 1327.13147       775   1.7124277   {txt}Root MSE        =   {res} .45488

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           inter{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .2095731{col 30}{space 2} .0364349{col 41}{space 1}    5.75{col 50}{space 3}0.000{col 58}{space 4} .1380488{col 71}{space 3} .2810975
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0275511{col 30}{space 2} .0274151{col 41}{space 1}   -1.00{col 50}{space 3}0.315{col 58}{space 4}-.0813689{col 71}{space 3} .0262666
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} 1.053982{col 30}{space 2} .0233987{col 41}{space 1}   45.04{col 50}{space 3}0.000{col 58}{space 4} 1.008048{col 71}{space 3} 1.099915
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0164632{col 30}{space 2} .0020965{col 41}{space 1}    7.85{col 50}{space 3}0.000{col 58}{space 4} .0123476{col 71}{space 3} .0205787
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-3.552667{col 30}{space 2}  .871262{col 41}{space 1}   -4.08{col 50}{space 3}0.000{col 58}{space 4}-5.263015{col 71}{space 3}-1.842318
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .1614054{col 30}{space 2}   .08522{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0058873{col 71}{space 3} .3286982
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0938887{col 30}{space 2}  .028449{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4} .0380414{col 71}{space 3} .1497361
{txt}{space 12}time {c |}{col 18}{res}{space 2} .0842824{col 30}{space 2} .0092446{col 41}{space 1}    9.12{col 50}{space 3}0.000{col 58}{space 4} .0661347{col 71}{space 3} .1024301
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0059734{col 30}{space 2} .0004885{col 41}{space 1}  -12.23{col 50}{space 3}0.000{col 58}{space 4}-.0069324{col 71}{space 3}-.0050145
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} .0250975{col 30}{space 2}   .03649{col 41}{space 1}    0.69{col 50}{space 3}0.492{col 58}{space 4} -.046535{col 71}{space 3}   .09673
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .2410883{col 30}{space 2} .2443411{col 41}{space 1}    0.99{col 50}{space 3}0.324{col 58}{space 4}-.2385703{col 71}{space 3} .7207469
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,188
{txt}{hline 13}{c +}{hline 34}   F(10, 1177)     = {res}   707.40
{txt}       Model {c |} {res}  6037.5975        10   603.75975   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 1004.55318     1,177  .853486137   {txt}R-squared       ={res}    0.8574
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8561
{txt}       Total {c |} {res} 7042.15069     1,187  5.93273015   {txt}Root MSE        =   {res} .92384

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.5795859{col 30}{space 2} .0612752{col 41}{space 1}   -9.46{col 50}{space 3}0.000{col 58}{space 4}-.6998066{col 71}{space 3}-.4593651
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0372851{col 30}{space 2}   .04641{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4}-.0537705{col 71}{space 3} .1283407
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0441181{col 30}{space 2} .0028629{col 41}{space 1}   15.41{col 50}{space 3}0.000{col 58}{space 4} .0385012{col 71}{space 3}  .049735
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-.0862367{col 30}{space 2} 1.418084{col 41}{space 1}   -0.06{col 50}{space 3}0.952{col 58}{space 4}-2.868491{col 71}{space 3} 2.696018
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .4816623{col 30}{space 2} .1395626{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4}  .207843{col 71}{space 3} .7554816
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0199244{col 30}{space 2} .0434799{col 41}{space 1}    0.46{col 50}{space 3}0.647{col 58}{space 4}-.0653824{col 71}{space 3} .1052311
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1152839{col 30}{space 2}  .012712{col 41}{space 1}   -9.07{col 50}{space 3}0.000{col 58}{space 4}-.1402246{col 71}{space 3}-.0903432
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0070824{col 30}{space 2} .0004937{col 41}{space 1}   14.34{col 50}{space 3}0.000{col 58}{space 4} .0061137{col 71}{space 3} .0080511
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0337592{col 30}{space 2} .0598774{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4}-.1512376{col 71}{space 3} .0837193
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .7787028{col 30}{space 2} .0150194{col 41}{space 1}   51.85{col 50}{space 3}0.000{col 58}{space 4}  .749235{col 71}{space 3} .8081706
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3466399{col 30}{space 2} .3984741{col 41}{space 1}    0.87{col 50}{space 3}0.385{col 58}{space 4}-.4351589{col 71}{space 3} 1.128439
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,392
{txt}{hline 13}{c +}{hline 34}   F(10, 1381)     = {res}  4428.09
{txt}       Model {c |} {res}  70600.173        10   7060.0173   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 2201.82791     1,381  1.59437213   {txt}R-squared       ={res}    0.9698
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9695
{txt}       Total {c |} {res} 72802.0009     1,391  52.3378871   {txt}Root MSE        =   {res} 1.2627

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.9826934{col 30}{space 2} .0750632{col 41}{space 1}  -13.09{col 50}{space 3}0.000{col 58}{space 4}-1.129944{col 71}{space 3}-.8354431
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0102529{col 30}{space 2} .0549554{col 41}{space 1}   -0.19{col 50}{space 3}0.852{col 58}{space 4}-.1180579{col 71}{space 3} .0975521
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0392272{col 30}{space 2}  .003057{col 41}{space 1}   12.83{col 50}{space 3}0.000{col 58}{space 4} .0332304{col 71}{space 3}  .045224
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} .1882402{col 30}{space 2} 1.796745{col 41}{space 1}    0.10{col 50}{space 3}0.917{col 58}{space 4}-3.336404{col 71}{space 3} 3.712884
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .6530161{col 30}{space 2} .1789386{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .3019952{col 71}{space 3} 1.004037
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0009161{col 30}{space 2} .0576138{col 41}{space 1}    0.02{col 50}{space 3}0.987{col 58}{space 4} -.112104{col 71}{space 3} .1139362
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1573401{col 30}{space 2} .0163688{col 41}{space 1}   -9.61{col 50}{space 3}0.000{col 58}{space 4}-.1894505{col 71}{space 3}-.1252296
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0087341{col 30}{space 2} .0006063{col 41}{space 1}   14.41{col 50}{space 3}0.000{col 58}{space 4} .0075448{col 71}{space 3} .0099235
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0899983{col 30}{space 2} .0752737{col 41}{space 1}   -1.20{col 50}{space 3}0.232{col 58}{space 4}-.2376615{col 71}{space 3}  .057665
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .9493809{col 30}{space 2} .0050782{col 41}{space 1}  186.95{col 50}{space 3}0.000{col 58}{space 4} .9394192{col 71}{space 3} .9593427
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .7469446{col 30}{space 2}  .504559{col 41}{space 1}    1.48{col 50}{space 3}0.139{col 58}{space 4}-.2428402{col 71}{space 3} 1.736729
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,392
{txt}{hline 13}{c +}{hline 34}   F(10, 1381)     = {res}  3977.36
{txt}       Model {c |} {res} 67682.1783        10  6768.21783   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 2350.02742     1,381  1.70168531   {txt}R-squared       ={res}    0.9664
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9662
{txt}       Total {c |} {res} 70032.2057     1,391  50.3466612   {txt}Root MSE        =   {res} 1.3045

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           inter{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} 1.077833{col 30}{space 2}  .076934{col 41}{space 1}   14.01{col 50}{space 3}0.000{col 58}{space 4} .9269132{col 71}{space 3} 1.228754
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0236304{col 30}{space 2} .0567719{col 41}{space 1}   -0.42{col 50}{space 3}0.677{col 58}{space 4}-.1349988{col 71}{space 3}  .087738
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} 1.013281{col 30}{space 2}   .00542{col 41}{space 1}  186.95{col 50}{space 3}0.000{col 58}{space 4} 1.002649{col 71}{space 3} 1.023914
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0368224{col 30}{space 2} .0031908{col 41}{space 1}  -11.54{col 50}{space 3}0.000{col 58}{space 4}-.0430818{col 71}{space 3} -.030563
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-.6260828{col 30}{space 2} 1.856158{col 41}{space 1}   -0.34{col 50}{space 3}0.736{col 58}{space 4}-4.267277{col 71}{space 3} 3.015111
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.6019809{col 30}{space 2} .1850441{col 41}{space 1}   -3.25{col 50}{space 3}0.001{col 58}{space 4}-.9649788{col 71}{space 3}-.2389831
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0102753{col 30}{space 2} .0595205{col 41}{space 1}    0.17{col 50}{space 3}0.863{col 58}{space 4}-.1064852{col 71}{space 3} .1270357
{txt}{space 12}time {c |}{col 18}{res}{space 2} .1513546{col 30}{space 2} .0169858{col 41}{space 1}    8.91{col 50}{space 3}0.000{col 58}{space 4} .1180338{col 71}{space 3} .1846754
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0083757{col 30}{space 2} .0006329{col 41}{space 1}  -13.23{col 50}{space 3}0.000{col 58}{space 4}-.0096172{col 71}{space 3}-.0071343
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}  .090248{col 30}{space 2} .0777681{col 41}{space 1}    1.16{col 50}{space 3}0.246{col 58}{space 4}-.0623083{col 71}{space 3} .2428043
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.6586356{col 30}{space 2}  .521375{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-1.681408{col 71}{space 3} .3641371
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,318
{txt}{hline 13}{c +}{hline 34}   F(10, 1307)     = {res}  7704.56
{txt}       Model {c |} {res} 69239.8019        10  6923.98019   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 1174.58262     1,307  .898686014   {txt}R-squared       ={res}    0.9833
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9832
{txt}       Total {c |} {res} 70414.3845     1,317  53.4657437   {txt}Root MSE        =   {res} .94799

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.7468247{col 30}{space 2} .0577576{col 41}{space 1}  -12.93{col 50}{space 3}0.000{col 58}{space 4}-.8601325{col 71}{space 3} -.633517
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0456669{col 30}{space 2} .0423469{col 41}{space 1}    1.08{col 50}{space 3}0.281{col 58}{space 4}-.0374084{col 71}{space 3} .1287423
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}  .003727{col 30}{space 2} .0027144{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0015981{col 71}{space 3} .0090521
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 1.541099{col 30}{space 2}  1.38762{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4}-1.181107{col 71}{space 3} 4.263306
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .2108995{col 30}{space 2} .1388873{col 41}{space 1}    1.52{col 50}{space 3}0.129{col 58}{space 4}-.0615669{col 71}{space 3}  .483366
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.0991476{col 30}{space 2} .0438305{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-.1851335{col 71}{space 3}-.0131617
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1624657{col 30}{space 2} .0127191{col 41}{space 1}  -12.77{col 50}{space 3}0.000{col 58}{space 4}-.1874178{col 71}{space 3}-.1375136
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}  .009297{col 30}{space 2} .0004847{col 41}{space 1}   19.18{col 50}{space 3}0.000{col 58}{space 4}  .008346{col 71}{space 3} .0102479
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0600151{col 30}{space 2} .0577739{col 41}{space 1}   -1.04{col 50}{space 3}0.299{col 58}{space 4}-.1733549{col 71}{space 3} .0533247
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .9665123{col 30}{space 2} .0038672{col 41}{space 1}  249.93{col 50}{space 3}0.000{col 58}{space 4} .9589257{col 71}{space 3} .9740989
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5971752{col 30}{space 2} .3886338{col 41}{space 1}    1.54{col 50}{space 3}0.125{col 58}{space 4} -.165239{col 71}{space 3} 1.359589
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,318
{txt}{hline 13}{c +}{hline 34}   F(10, 1307)     = {res}  7216.30
{txt}       Model {c |} {res} 68000.8183        10  6800.08183   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 1231.61564     1,307    .9423226   {txt}R-squared       ={res}    0.9822
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9821
{txt}       Total {c |} {res} 69232.4339     1,317  52.5682869   {txt}Root MSE        =   {res} .97073

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           inter{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .7943812{col 30}{space 2} .0588436{col 41}{space 1}   13.50{col 50}{space 3}0.000{col 58}{space 4}  .678943{col 71}{space 3} .9098193
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0654412{col 30}{space 2} .0433443{col 41}{space 1}   -1.51{col 50}{space 3}0.131{col 58}{space 4}-.1504733{col 71}{space 3} .0195908
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} 1.013442{col 30}{space 2}  .004055{col 41}{space 1}  249.93{col 50}{space 3}0.000{col 58}{space 4} 1.005487{col 71}{space 3} 1.021397
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} -.001252{col 30}{space 2} .0027813{col 41}{space 1}   -0.45{col 50}{space 3}0.653{col 58}{space 4}-.0067083{col 71}{space 3} .0042044
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-1.891029{col 30}{space 2} 1.420617{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-4.677968{col 71}{space 3} .8959108
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.1754897{col 30}{space 2} .1422619{col 41}{space 1}   -1.23{col 50}{space 3}0.218{col 58}{space 4}-.4545762{col 71}{space 3} .1035969
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .1085036{col 30}{space 2} .0448696{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4} .0204794{col 71}{space 3} .1965278
{txt}{space 12}time {c |}{col 18}{res}{space 2} .1599993{col 30}{space 2} .0130851{col 41}{space 1}   12.23{col 50}{space 3}0.000{col 58}{space 4} .1343293{col 71}{space 3} .1856694
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0091583{col 30}{space 2} .0005015{col 41}{space 1}  -18.26{col 50}{space 3}0.000{col 58}{space 4}-.0101422{col 71}{space 3}-.0081745
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} .0593964{col 30}{space 2} .0591615{col 41}{space 1}    1.00{col 50}{space 3}0.316{col 58}{space 4}-.0566656{col 71}{space 3} .1754584
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.5323954{col 30}{space 2} .3980442{col 41}{space 1}   -1.34{col 50}{space 3}0.181{col 58}{space 4}-1.313271{col 71}{space 3} .2484799
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,130
{txt}{hline 13}{c +}{hline 34}   F(10, 1119)     = {res}   468.04
{txt}       Model {c |} {res} 1876.10505        10  187.610505   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 448.546423     1,119  .400845775   {txt}R-squared       ={res}    0.8070
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8053
{txt}       Total {c |} {res} 2324.65147     1,129  2.05903584   {txt}Root MSE        =   {res} .63312

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} -.195919{col 30}{space 2} .0436467{col 41}{space 1}   -4.49{col 50}{space 3}0.000{col 58}{space 4}-.2815575{col 71}{space 3}-.1102805
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0088662{col 30}{space 2} .0310623{col 41}{space 1}    0.29{col 50}{space 3}0.775{col 58}{space 4}-.0520808{col 71}{space 3} .0698132
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0800946{col 30}{space 2} .0056046{col 41}{space 1}   14.29{col 50}{space 3}0.000{col 58}{space 4} .0690978{col 71}{space 3} .0910914
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 1.964488{col 30}{space 2} 1.003914{col 41}{space 1}    1.96{col 50}{space 3}0.051{col 58}{space 4}-.0052776{col 71}{space 3} 3.934253
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .6342029{col 30}{space 2} .0984669{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .4410024{col 71}{space 3} .8274034
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0791334{col 30}{space 2} .0315061{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0173156{col 71}{space 3} .1409511
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.0963386{col 30}{space 2} .0098335{col 41}{space 1}   -9.80{col 50}{space 3}0.000{col 58}{space 4}-.1156328{col 71}{space 3}-.0770444
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0061923{col 30}{space 2} .0004438{col 41}{space 1}   13.95{col 50}{space 3}0.000{col 58}{space 4} .0053215{col 71}{space 3}  .007063
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0059928{col 30}{space 2} .0413089{col 41}{space 1}   -0.15{col 50}{space 3}0.885{col 58}{space 4}-.0870445{col 71}{space 3} .0750588
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .6183614{col 30}{space 2} .0212624{col 41}{space 1}   29.08{col 50}{space 3}0.000{col 58}{space 4} .5766427{col 71}{space 3} .6600802
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.4715995{col 30}{space 2} .2827918{col 41}{space 1}   -1.67{col 50}{space 3}0.096{col 58}{space 4}-1.026461{col 71}{space 3} .0832623
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       946
{txt}{hline 13}{c +}{hline 34}   F(10, 935)      = {res}  1436.81
{txt}       Model {c |} {res} 536.731132        10  53.6731132   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 34.9275887       935   .03735571   {txt}R-squared       ={res}    0.9389
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9382
{txt}       Total {c |} {res}  571.65872       945  .604929863   {txt}Root MSE        =   {res} .19328

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.0642756{col 30}{space 2}  .014475{col 41}{space 1}   -4.44{col 50}{space 3}0.000{col 58}{space 4}-.0926829{col 71}{space 3}-.0358684
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0117019{col 30}{space 2}  .010325{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4} -.008561{col 71}{space 3} .0319648
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0514081{col 30}{space 2} .0052701{col 41}{space 1}    9.75{col 50}{space 3}0.000{col 58}{space 4} .0410656{col 71}{space 3} .0617507
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} .1265303{col 30}{space 2} .3331887{col 41}{space 1}    0.38{col 50}{space 3}0.704{col 58}{space 4} -.527354{col 71}{space 3} .7804147
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .2082319{col 30}{space 2} .0339881{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .1415302{col 71}{space 3} .2749337
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0422739{col 30}{space 2} .0108331{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .0210139{col 71}{space 3} .0635338
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.0469998{col 30}{space 2} .0038026{col 41}{space 1}  -12.36{col 50}{space 3}0.000{col 58}{space 4}-.0544624{col 71}{space 3}-.0395371
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0034623{col 30}{space 2} .0002074{col 41}{space 1}   16.70{col 50}{space 3}0.000{col 58}{space 4} .0030554{col 71}{space 3} .0038692
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}  .003018{col 30}{space 2} .0138043{col 41}{space 1}    0.22{col 50}{space 3}0.827{col 58}{space 4} -.024073{col 71}{space 3}  .030109
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .7634448{col 30}{space 2} .0107332{col 41}{space 1}   71.13{col 50}{space 3}0.000{col 58}{space 4} .7423808{col 71}{space 3} .7845088
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0805367{col 30}{space 2} .0945515{col 41}{space 1}   -0.85{col 50}{space 3}0.395{col 58}{space 4}-.2660945{col 71}{space 3} .1050211
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       946
{txt}{hline 13}{c +}{hline 34}   F(10, 935)      = {res}   806.80
{txt}       Model {c |} {res} 436.433408        10  43.6433408   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 50.5784679       935  .054094618   {txt}R-squared       ={res}    0.8961
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8950
{txt}       Total {c |} {res} 487.011876       945  .515356483   {txt}Root MSE        =   {res} .23258

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           inter{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .1206229{col 30}{space 2} .0171537{col 41}{space 1}    7.03{col 50}{space 3}0.000{col 58}{space 4} .0869586{col 71}{space 3} .1542871
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0020451{col 30}{space 2} .0124332{col 41}{space 1}   -0.16{col 50}{space 3}0.869{col 58}{space 4}-.0264452{col 71}{space 3}  .022355
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} 1.105541{col 30}{space 2} .0155428{col 41}{space 1}   71.13{col 50}{space 3}0.000{col 58}{space 4} 1.075038{col 71}{space 3} 1.136043
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0390632{col 30}{space 2}  .006533{col 41}{space 1}   -5.98{col 50}{space 3}0.000{col 58}{space 4}-.0518843{col 71}{space 3}-.0262422
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} .5398373{col 30}{space 2} .4005908{col 41}{space 1}    1.35{col 50}{space 3}0.178{col 58}{space 4} -.246324{col 71}{space 3} 1.325999
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.1712166{col 30}{space 2} .0413355{col 41}{space 1}   -4.14{col 50}{space 3}0.000{col 58}{space 4}-.2523377{col 71}{space 3}-.0900954
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.0452708{col 30}{space 2} .0130582{col 41}{space 1}   -3.47{col 50}{space 3}0.001{col 58}{space 4}-.0708977{col 71}{space 3} -.019644
{txt}{space 12}time {c |}{col 18}{res}{space 2} .0473009{col 30}{space 2}  .004687{col 41}{space 1}   10.09{col 50}{space 3}0.000{col 58}{space 4} .0381027{col 71}{space 3} .0564991
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0034752{col 30}{space 2} .0002606{col 41}{space 1}  -13.34{col 50}{space 3}0.000{col 58}{space 4}-.0039866{col 71}{space 3}-.0029638
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0072311{col 30}{space 2} .0166104{col 41}{space 1}   -0.44{col 50}{space 3}0.663{col 58}{space 4}-.0398291{col 71}{space 3} .0253669
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.1084993{col 30}{space 2} .1137691{col 41}{space 1}   -0.95{col 50}{space 3}0.340{col 58}{space 4}-.3317716{col 71}{space 3} .1147731
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,238
{txt}{hline 13}{c +}{hline 34}   F(10, 1227)     = {res}  1051.56
{txt}       Model {c |} {res} 10857.3825        10  1085.73825   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 1266.88351     1,227  1.03250489   {txt}R-squared       ={res}    0.8955
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8947
{txt}       Total {c |} {res}  12124.266     1,237  9.80134679   {txt}Root MSE        =   {res} 1.0161

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.4859101{col 30}{space 2} .0662597{col 41}{space 1}   -7.33{col 50}{space 3}0.000{col 58}{space 4}-.6159049{col 71}{space 3}-.3559152
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0042684{col 30}{space 2} .0470276{col 41}{space 1}   -0.09{col 50}{space 3}0.928{col 58}{space 4}-.0965317{col 71}{space 3}  .087995
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0223363{col 30}{space 2} .0026558{col 41}{space 1}    8.41{col 50}{space 3}0.000{col 58}{space 4} .0171259{col 71}{space 3} .0275467
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-.2602179{col 30}{space 2} 1.528266{col 41}{space 1}   -0.17{col 50}{space 3}0.865{col 58}{space 4}-3.258522{col 71}{space 3} 2.738086
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .0578865{col 30}{space 2} .1542499{col 41}{space 1}    0.38{col 50}{space 3}0.708{col 58}{space 4}-.2447361{col 71}{space 3} .3605092
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.1148483{col 30}{space 2} .0485527{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.2101039{col 71}{space 3}-.0195928
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1797758{col 30}{space 2} .0138728{col 41}{space 1}  -12.96{col 50}{space 3}0.000{col 58}{space 4}-.2069929{col 71}{space 3}-.1525587
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0105525{col 30}{space 2} .0005432{col 41}{space 1}   19.42{col 50}{space 3}0.000{col 58}{space 4} .0094867{col 71}{space 3} .0116183
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0405708{col 30}{space 2} .0645646{col 41}{space 1}   -0.63{col 50}{space 3}0.530{col 58}{space 4}-.1672401{col 71}{space 3} .0860984
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .8102712{col 30}{space 2} .0119476{col 41}{space 1}   67.82{col 50}{space 3}0.000{col 58}{space 4} .7868312{col 71}{space 3} .8337111
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.064612{col 30}{space 2} .4270119{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .2268582{col 71}{space 3} 1.902367
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,238
{txt}{hline 13}{c +}{hline 34}   F(10, 1227)     = {res}   686.13
{txt}       Model {c |} {res} 8517.96283        10  851.796283   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 1523.26994     1,227  1.24145879   {txt}R-squared       ={res}    0.8483
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8471
{txt}       Total {c |} {res} 10041.2328     1,237  8.11740725   {txt}Root MSE        =   {res} 1.1142

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           inter{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} .8239963{col 30}{space 2}  .070405{col 41}{space 1}   11.70{col 50}{space 3}0.000{col 58}{space 4} .6858689{col 71}{space 3} .9621238
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .1051587{col 30}{space 2} .0514798{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0041605{col 71}{space 3} .2061569
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} .9742504{col 30}{space 2} .0143655{col 41}{space 1}   67.82{col 50}{space 3}0.000{col 58}{space 4} .9460668{col 71}{space 3} 1.002434
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0166378{col 30}{space 2}  .002957{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.0224392{col 71}{space 3}-.0108364
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-1.032074{col 30}{space 2} 1.675549{col 41}{space 1}   -0.62{col 50}{space 3}0.538{col 58}{space 4}-4.319332{col 71}{space 3} 2.255184
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .1700836{col 30}{space 2} .1690794{col 41}{space 1}    1.01{col 50}{space 3}0.315{col 58}{space 4}-.1616332{col 71}{space 3} .5018004
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .1855401{col 30}{space 2} .0530972{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .0813687{col 71}{space 3} .2897114
{txt}{space 12}time {c |}{col 18}{res}{space 2} .1422211{col 30}{space 2} .0157032{col 41}{space 1}    9.06{col 50}{space 3}0.000{col 58}{space 4}  .111413{col 71}{space 3} .1730291
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} -.008142{col 30}{space 2} .0006403{col 41}{space 1}  -12.72{col 50}{space 3}0.000{col 58}{space 4}-.0093981{col 71}{space 3}-.0068859
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} .0305087{col 30}{space 2}  .070803{col 41}{space 1}    0.43{col 50}{space 3}0.667{col 58}{space 4}-.1083996{col 71}{space 3} .1694171
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-1.294122{col 30}{space 2} .4679593{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4}-2.212211{col 71}{space 3} -.376033
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,367
{txt}{hline 13}{c +}{hline 34}   F(10, 1356)     = {res}  5261.46
{txt}       Model {c |} {res} 78034.7796        10  7803.47796   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 2011.13829     1,356  1.48314033   {txt}R-squared       ={res}    0.9749
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9747
{txt}       Total {c |} {res} 80045.9179     1,366  58.5987686   {txt}Root MSE        =   {res} 1.2178

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.9401644{col 30}{space 2} .0731276{col 41}{space 1}  -12.86{col 50}{space 3}0.000{col 58}{space 4} -1.08362{col 71}{space 3} -.796709
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .0004082{col 30}{space 2} .0522115{col 41}{space 1}    0.01{col 50}{space 3}0.994{col 58}{space 4}-.1020158{col 71}{space 3} .1028322
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0436339{col 30}{space 2} .0032685{col 41}{space 1}   13.35{col 50}{space 3}0.000{col 58}{space 4}  .037222{col 71}{space 3} .0500458
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-2.243542{col 30}{space 2} 1.740843{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4} -5.65858{col 71}{space 3} 1.171496
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2} .6140411{col 30}{space 2} .1766043{col 41}{space 1}    3.48{col 50}{space 3}0.001{col 58}{space 4} .2675938{col 71}{space 3} .9604884
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0076278{col 30}{space 2} .0562281{col 41}{space 1}    0.14{col 50}{space 3}0.892{col 58}{space 4}-.1026757{col 71}{space 3} .1179314
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1264657{col 30}{space 2} .0157177{col 41}{space 1}   -8.05{col 50}{space 3}0.000{col 58}{space 4}-.1572995{col 71}{space 3} -.095632
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0072531{col 30}{space 2} .0005798{col 41}{space 1}   12.51{col 50}{space 3}0.000{col 58}{space 4} .0061157{col 71}{space 3} .0083906
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0483365{col 30}{space 2} .0737934{col 41}{space 1}   -0.66{col 50}{space 3}0.513{col 58}{space 4}-.1930981{col 71}{space 3} .0964251
{txt}{space 11}inter {c |}{col 18}{res}{space 2}  .947082{col 30}{space 2}  .004739{col 41}{space 1}  199.85{col 50}{space 3}0.000{col 58}{space 4} .9377854{col 71}{space 3} .9563786
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.111453{col 30}{space 2} .4892877{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .1516104{col 71}{space 3} 2.071296
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,367
{txt}{hline 13}{c +}{hline 34}   F(10, 1356)     = {res}  4741.26
{txt}       Model {c |} {res} 75822.9773        10  7582.29773   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 2168.53558     1,356  1.59921503   {txt}R-squared       ={res}    0.9722
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9720
{txt}       Total {c |} {res} 77991.5129     1,366  57.0948118   {txt}Root MSE        =   {res} 1.2646

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           inter{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2} 1.042726{col 30}{space 2} .0752808{col 41}{space 1}   13.85{col 50}{space 3}0.000{col 58}{space 4} .8950469{col 71}{space 3} 1.190406
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2}-.0186203{col 30}{space 2} .0542137{col 41}{space 1}   -0.34{col 50}{space 3}0.731{col 58}{space 4}-.1249721{col 71}{space 3} .0877316
{txt}{space 9}per100k {c |}{col 18}{res}{space 2} 1.021203{col 30}{space 2} .0051099{col 41}{space 1}  199.85{col 50}{space 3}0.000{col 58}{space 4} 1.011179{col 71}{space 3} 1.031227
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2}-.0409157{col 30}{space 2} .0034349{col 41}{space 1}  -11.91{col 50}{space 3}0.000{col 58}{space 4} -.047654{col 71}{space 3}-.0341773
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2} 1.882555{col 30}{space 2} 1.808066{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-1.664354{col 71}{space 3} 5.429464
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}-.5784968{col 30}{space 2} .1835294{col 41}{space 1}   -3.15{col 50}{space 3}0.002{col 58}{space 4}-.9385292{col 71}{space 3}-.2184644
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2} .0045279{col 30}{space 2} .0583872{col 41}{space 1}    0.08{col 50}{space 3}0.938{col 58}{space 4}-.1100112{col 71}{space 3}  .119067
{txt}{space 12}time {c |}{col 18}{res}{space 2} .1200593{col 30}{space 2}  .016385{col 41}{space 1}    7.33{col 50}{space 3}0.000{col 58}{space 4} .0879166{col 71}{space 3} .1522021
{txt}{space 10}timesq {c |}{col 18}{res}{space 2}-.0068937{col 30}{space 2} .0006077{col 41}{space 1}  -11.34{col 50}{space 3}0.000{col 58}{space 4}-.0080859{col 71}{space 3}-.0057016
{txt}{space 9}weekend {c |}{col 18}{res}{space 2} .0454609{col 30}{space 2} .0766288{col 41}{space 1}    0.59{col 50}{space 3}0.553{col 58}{space 4} -.104863{col 71}{space 3} .1957847
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-1.069743{col 30}{space 2} .5082098{col 41}{space 1}   -2.10{col 50}{space 3}0.035{col 58}{space 4}-2.066706{col 71}{space 3}-.0727806
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,344
{txt}{hline 13}{c +}{hline 34}   F(10, 1333)     = {res}   824.40
{txt}       Model {c |} {res} 10286.0785        10  1028.60785   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  1663.1853     1,333   1.2477009   {txt}R-squared       ={res}    0.8608
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.8598
{txt}       Total {c |} {res} 11949.2638     1,343  8.89744138   {txt}Root MSE        =   {res}  1.117

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         per100k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}gov {c |}{col 18}{res}{space 2}-.5914583{col 30}{space 2} .0714037{col 41}{space 1}   -8.28{col 50}{space 3}0.000{col 58}{space 4}-.7315341{col 71}{space 3}-.4513825
{txt}{space 8}stategdp {c |}{col 18}{res}{space 2} .1575253{col 30}{space 2} .0492394{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4} .0609301{col 71}{space 3} .2541205
{txt}{space 8}neighbor {c |}{col 18}{res}{space 2} .0426252{col 30}{space 2}  .002609{col 41}{space 1}   16.34{col 50}{space 3}0.000{col 58}{space 4} .0375069{col 71}{space 3} .0477434
{txt}{space 11}pop65 {c |}{col 18}{res}{space 2}-1.193345{col 30}{space 2} 1.602229{col 41}{space 1}   -0.74{col 50}{space 3}0.457{col 58}{space 4} -4.33651{col 71}{space 3}  1.94982
{txt}{space 6}popcon2016 {c |}{col 18}{res}{space 2}   .63373{col 30}{space 2}  .167422{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .3052906{col 71}{space 3} .9621693
{txt}hospitalbeds2018 {c |}{col 18}{res}{space 2}-.0000119{col 30}{space 2} .0516727{col 41}{space 1}   -0.00{col 50}{space 3}1.000{col 58}{space 4}-.1013806{col 71}{space 3} .1013568
{txt}{space 12}time {c |}{col 18}{res}{space 2}-.1761319{col 30}{space 2} .0145959{col 41}{space 1}  -12.07{col 50}{space 3}0.000{col 58}{space 4}-.2047653{col 71}{space 3}-.1474985
{txt}{space 10}timesq {c |}{col 18}{res}{space 2} .0102534{col 30}{space 2} .0005499{col 41}{space 1}   18.65{col 50}{space 3}0.000{col 58}{space 4} .0091747{col 71}{space 3} .0113321
{txt}{space 9}weekend {c |}{col 18}{res}{space 2}-.0750078{col 30}{space 2} .0681523{col 41}{space 1}   -1.10{col 50}{space 3}0.271{col 58}{space 4}-.2087054{col 71}{space 3} .0586897
{txt}{space 11}inter {c |}{col 18}{res}{space 2} .7212964{col 30}{space 2} .0142808{col 41}{space 1}   50.51{col 50}{space 3}0.000{col 58}{space 4} .6932811{col 71}{space 3} .7493116
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5621671{col 30}{space 2} .4484691{col 41}{space 1}    1.25{col 50}{space 3}0.210{col 58}{space 4} -.317615{col 71}{space 3} 1.441949
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS inter XXXXXXXXXXXXXXXXXXXXXXXXXXXX
{txt}
{com}. 
. *MULTICOLLINEARITY ANALYSIS, NO INTERACTION
. *Don't report time and timesq, as they're going to be highly collinear with each other.
. local xs gov stategdp per100k neighbor pop65 popcon2016 hospitalbeds2018 time timesq weekend
{txt}
{com}. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. foreach x of local xs {c -(}
{txt}  4{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS `x' XXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  5{com}. local otherxs: list xs - x
{txt}  6{com}. quietly reg `x' `otherxs' if `v'!=.&date>226&date<327
{txt}  7{com}. local r2=e(r2)
{txt}  8{com}. if `r2'>.8&"`x'"!="time"&"`x'"!="timesq" reg `x' `otherxs' if `v'!=.&date>226&date<327
{txt}  9{com}. {c )-}
{txt} 10{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Y IS eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS gov XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS stategdp XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS per100k XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS neighbor XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS pop65 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS popcon2016 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS hospitalbeds2018 XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS time XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS timesq XXXXXXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXXXXXXXXXXXXX X IS weekend XXXXXXXXXXXXXXXXXXXXXXXXXXXX
{txt}
{com}. 
. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF RACE XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{res}XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF RACE XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
{txt}
{com}. foreach v of local vs {c -(}
{txt}  2{com}. di "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF `v' XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
{txt}  3{com}. logit `v' black2018 hisp2018 per100k neighbor popcon2016 time timesq weekend if date>226&date<327
{txt}  4{com}. {c )-}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF soemergency XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-169.00668}  
Iteration 1:{space 3}log likelihood = {res:-147.00001}  
Iteration 2:{space 3}log likelihood = {res:-138.65096}  
Iteration 3:{space 3}log likelihood = {res:-137.72134}  
Iteration 4:{space 3}log likelihood = {res: -137.6493}  
Iteration 5:{space 3}log likelihood = {res:-137.64818}  
Iteration 6:{space 3}log likelihood = {res:-137.64818}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       776
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     62.72
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-137.64818{txt}{col 49}Pseudo R2{col 67}= {res}    0.1855

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} soemergency{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2}-.5020028{col 26}{space 2} 1.805478{col 37}{space 1}   -0.28{col 46}{space 3}0.781{col 54}{space 4}-4.040676{col 67}{space 3}  3.03667
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2} 3.155717{col 26}{space 2} 1.451952{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} .3099437{col 67}{space 3} 6.001491
{txt}{space 5}per100k {c |}{col 14}{res}{space 2}-1.257938{col 26}{space 2} .9010754{col 37}{space 1}   -1.40{col 46}{space 3}0.163{col 54}{space 4}-3.024013{col 67}{space 3} .5081372
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2} -.042892{col 26}{space 2} .1380695{col 37}{space 1}   -0.31{col 46}{space 3}0.756{col 54}{space 4}-.3135033{col 67}{space 3} .2277193
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2}-.0351585{col 26}{space 2} .7935743{col 37}{space 1}   -0.04{col 46}{space 3}0.965{col 54}{space 4}-1.590535{col 67}{space 3} 1.520218
{txt}{space 8}time {c |}{col 14}{res}{space 2}  .526066{col 26}{space 2}  .205643{col 37}{space 1}    2.56{col 46}{space 3}0.011{col 54}{space 4} .1230131{col 67}{space 3} .9291188
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.0107518{col 26}{space 2} .0094924{col 37}{space 1}   -1.13{col 46}{space 3}0.257{col 54}{space 4}-.0293565{col 67}{space 3}  .007853
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-.5987068{col 26}{space 2} .4344355{col 37}{space 1}   -1.38{col 46}{space 3}0.168{col 54}{space 4}-1.450185{col 67}{space 3}  .252771
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-6.829226{col 26}{space 2} 1.205576{col 37}{space 1}   -5.66{col 46}{space 3}0.000{col 54}{space 4}-9.192111{col 67}{space 3}-4.466341
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 2 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF natguard XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-121.26385}  
Iteration 1:{space 3}log likelihood = {res:-106.93362}  
Iteration 2:{space 3}log likelihood = {res:-99.629706}  
Iteration 3:{space 3}log likelihood = {res:-98.765975}  
Iteration 4:{space 3}log likelihood = {res: -98.74272}  
Iteration 5:{space 3}log likelihood = {res:-98.742665}  
Iteration 6:{space 3}log likelihood = {res:-98.742665}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,188
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     45.04
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-98.742665{txt}{col 49}Pseudo R2{col 67}= {res}    0.1857

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    natguard{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2}  8.01018{col 26}{space 2} 2.326248{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} 3.450818{col 67}{space 3} 12.56954
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2} 3.050027{col 26}{space 2} 1.967565{col 37}{space 1}    1.55{col 46}{space 3}0.121{col 54}{space 4}-.8063302{col 67}{space 3} 6.906383
{txt}{space 5}per100k {c |}{col 14}{res}{space 2}-.1238506{col 26}{space 2} .1676024{col 37}{space 1}   -0.74{col 46}{space 3}0.460{col 54}{space 4}-.4523452{col 67}{space 3}  .204644
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2} -.031206{col 26}{space 2} .0754729{col 37}{space 1}   -0.41{col 46}{space 3}0.679{col 54}{space 4}-.1791302{col 67}{space 3} .1167182
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2} 1.720515{col 26}{space 2} .8313121{col 37}{space 1}    2.07{col 46}{space 3}0.038{col 54}{space 4} .0911729{col 67}{space 3} 3.349857
{txt}{space 8}time {c |}{col 14}{res}{space 2} .6716028{col 26}{space 2} .2702901{col 37}{space 1}    2.48{col 46}{space 3}0.013{col 54}{space 4}  .141844{col 67}{space 3} 1.201362
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.0148314{col 26}{space 2} .0084841{col 37}{space 1}   -1.75{col 46}{space 3}0.080{col 54}{space 4}-.0314599{col 67}{space 3}  .001797
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-.6830039{col 26}{space 2} .5593601{col 37}{space 1}   -1.22{col 46}{space 3}0.222{col 54}{space 4}-1.779329{col 67}{space 3} .4133218
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-11.79911{col 26}{space 2} 2.332931{col 37}{space 1}   -5.06{col 46}{space 3}0.000{col 54}{space 4}-16.37157{col 67}{space 3}-7.226649
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF stayathome XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.45684}  
Iteration 1:{space 3}log likelihood = {res:-82.396546}  
Iteration 2:{space 3}log likelihood = {res:-75.835934}  
Iteration 3:{space 3}log likelihood = {res:-74.127572}  
Iteration 4:{space 3}log likelihood = {res:-71.146622}  
Iteration 5:{space 3}log likelihood = {res:-68.772172}  
Iteration 6:{space 3}log likelihood = {res:-68.049216}  
Iteration 7:{space 3}log likelihood = {res:-68.039102}  
Iteration 8:{space 3}log likelihood = {res:-68.039084}  
Iteration 9:{space 3}log likelihood = {res:-68.039084}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,392
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     64.84
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-68.039084{txt}{col 49}Pseudo R2{col 67}= {res}    0.3227

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  stayathome{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2}-3.031044{col 26}{space 2} 2.981294{col 37}{space 1}   -1.02{col 46}{space 3}0.309{col 54}{space 4}-8.874272{col 67}{space 3} 2.812185
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2}  1.96925{col 26}{space 2} 2.154325{col 37}{space 1}    0.91{col 46}{space 3}0.361{col 54}{space 4}-2.253149{col 67}{space 3}  6.19165
{txt}{space 5}per100k {c |}{col 14}{res}{space 2} .0021942{col 26}{space 2} .0173432{col 37}{space 1}    0.13{col 46}{space 3}0.899{col 54}{space 4}-.0317978{col 67}{space 3} .0361861
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2}-.0005718{col 26}{space 2} .0105295{col 37}{space 1}   -0.05{col 46}{space 3}0.957{col 54}{space 4}-.0212093{col 67}{space 3} .0200657
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2}-.3759363{col 26}{space 2} 1.090309{col 37}{space 1}   -0.34{col 46}{space 3}0.730{col 54}{space 4}-2.512903{col 67}{space 3}  1.76103
{txt}{space 8}time {c |}{col 14}{res}{space 2} 8.424016{col 26}{space 2} 3.186405{col 37}{space 1}    2.64{col 46}{space 3}0.008{col 54}{space 4} 2.178777{col 67}{space 3} 14.66925
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.1683671{col 26}{space 2} .0653426{col 37}{space 1}   -2.58{col 46}{space 3}0.010{col 54}{space 4}-.2964363{col 67}{space 3}-.0402979
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-.7886462{col 26}{space 2} .6673884{col 37}{space 1}   -1.18{col 46}{space 3}0.237{col 54}{space 4}-2.096703{col 67}{space 3} .5194111
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-107.1465{col 26}{space 2}  38.7098{col 37}{space 1}   -2.77{col 46}{space 3}0.006{col 54}{space 4}-183.0163{col 67}{space 3}-31.27669
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 799 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF gather XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-146.87893}  
Iteration 1:{space 3}log likelihood = {res:-123.63162}  
Iteration 2:{space 3}log likelihood = {res:-112.37568}  
Iteration 3:{space 3}log likelihood = {res:-109.24987}  
Iteration 4:{space 3}log likelihood = {res: -106.0066}  
Iteration 5:{space 3}log likelihood = {res: -104.5463}  
Iteration 6:{space 3}log likelihood = {res:-104.23211}  
Iteration 7:{space 3}log likelihood = {res:-104.22707}  
Iteration 8:{space 3}log likelihood = {res:-104.22706}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,318
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     85.30
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-104.22706{txt}{col 49}Pseudo R2{col 67}= {res}    0.2904

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      gather{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2} -1.13245{col 26}{space 2} 2.146417{col 37}{space 1}   -0.53{col 46}{space 3}0.598{col 54}{space 4} -5.33935{col 67}{space 3}  3.07445
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2} 2.712561{col 26}{space 2} 2.142339{col 37}{space 1}    1.27{col 46}{space 3}0.205{col 54}{space 4}-1.486347{col 67}{space 3} 6.911469
{txt}{space 5}per100k {c |}{col 14}{res}{space 2}-.0048013{col 26}{space 2} .0156141{col 37}{space 1}   -0.31{col 46}{space 3}0.758{col 54}{space 4}-.0354045{col 67}{space 3} .0258018
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2} .0076321{col 26}{space 2} .0074897{col 37}{space 1}    1.02{col 46}{space 3}0.308{col 54}{space 4}-.0070475{col 67}{space 3} .0223116
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2}-.6137958{col 26}{space 2} .8965897{col 37}{space 1}   -0.68{col 46}{space 3}0.494{col 54}{space 4}-2.371079{col 67}{space 3} 1.143488
{txt}{space 8}time {c |}{col 14}{res}{space 2} 2.632214{col 26}{space 2} 1.104881{col 37}{space 1}    2.38{col 46}{space 3}0.017{col 54}{space 4} .4666874{col 67}{space 3} 4.797741
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.0525623{col 26}{space 2} .0238934{col 37}{space 1}   -2.20{col 46}{space 3}0.028{col 54}{space 4}-.0993926{col 67}{space 3} -.005732
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-.5812051{col 26}{space 2} .5051195{col 37}{space 1}   -1.15{col 46}{space 3}0.250{col 54}{space 4}-1.571221{col 67}{space 3} .4088108
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -34.8468{col 26}{space 2} 12.66661{col 37}{space 1}   -2.75{col 46}{space 3}0.006{col 54}{space 4}-59.67289{col 67}{space 3}-10.02071
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 399 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF bars XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-179.48635}  
Iteration 1:{space 3}log likelihood = {res:-151.52627}  
Iteration 2:{space 3}log likelihood = {res:-132.60009}  
Iteration 3:{space 3}log likelihood = {res: -123.6279}  
Iteration 4:{space 3}log likelihood = {res:-118.63438}  
Iteration 5:{space 3}log likelihood = {res:-118.06325}  
Iteration 6:{space 3}log likelihood = {res:-118.05601}  
Iteration 7:{space 3}log likelihood = {res:  -118.056}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,130
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}    122.86
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}  -118.056{txt}{col 49}Pseudo R2{col 67}= {res}    0.3423

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        bars{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2}-1.065858{col 26}{space 2} 1.757662{col 37}{space 1}   -0.61{col 46}{space 3}0.544{col 54}{space 4}-4.510812{col 67}{space 3} 2.379097
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2}-2.680657{col 26}{space 2} 1.887367{col 37}{space 1}   -1.42{col 46}{space 3}0.156{col 54}{space 4}-6.379828{col 67}{space 3} 1.018514
{txt}{space 5}per100k {c |}{col 14}{res}{space 2} .2645151{col 26}{space 2}  .133994{col 37}{space 1}    1.97{col 46}{space 3}0.048{col 54}{space 4} .0018916{col 67}{space 3} .5271385
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2} .0184856{col 26}{space 2} .0242308{col 37}{space 1}    0.76{col 46}{space 3}0.446{col 54}{space 4}-.0290059{col 67}{space 3} .0659772
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2}-.5506605{col 26}{space 2}  .796562{col 37}{space 1}   -0.69{col 46}{space 3}0.489{col 54}{space 4}-2.111893{col 67}{space 3} 1.010572
{txt}{space 8}time {c |}{col 14}{res}{space 2}  2.68068{col 26}{space 2} .5713637{col 37}{space 1}    4.69{col 46}{space 3}0.000{col 54}{space 4} 1.560827{col 67}{space 3} 3.800532
{txt}{space 6}timesq {c |}{col 14}{res}{space 2} -.065213{col 26}{space 2} .0144104{col 37}{space 1}   -4.53{col 46}{space 3}0.000{col 54}{space 4}-.0934569{col 67}{space 3} -.036969
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-1.305734{col 26}{space 2} .5049845{col 37}{space 1}   -2.59{col 46}{space 3}0.010{col 54}{space 4}-2.295485{col 67}{space 3}-.3159825
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-28.58427{col 26}{space 2} 5.695775{col 37}{space 1}   -5.02{col 46}{space 3}0.000{col 54}{space 4}-39.74779{col 67}{space 3}-17.42076
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 254 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF school XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-177.95483}  
Iteration 1:{space 3}log likelihood = {res:-141.28426}  
Iteration 2:{space 3}log likelihood = {res:-122.93859}  
Iteration 3:{space 3}log likelihood = {res:-115.35504}  
Iteration 4:{space 3}log likelihood = {res:-110.66877}  
Iteration 5:{space 3}log likelihood = {res:-110.37388}  
Iteration 6:{space 3}log likelihood = {res:-110.36974}  
Iteration 7:{space 3}log likelihood = {res:-110.36974}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       946
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}    135.17
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-110.36974{txt}{col 49}Pseudo R2{col 67}= {res}    0.3798

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      school{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2} 2.252347{col 26}{space 2} 1.744728{col 37}{space 1}    1.29{col 46}{space 3}0.197{col 54}{space 4}-1.167257{col 67}{space 3}  5.67195
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2}-1.409868{col 26}{space 2}  1.88248{col 37}{space 1}   -0.75{col 46}{space 3}0.454{col 54}{space 4} -5.09946{col 67}{space 3} 2.279725
{txt}{space 5}per100k {c |}{col 14}{res}{space 2} .2413986{col 26}{space 2} .2783109{col 37}{space 1}    0.87{col 46}{space 3}0.386{col 54}{space 4}-.3040807{col 67}{space 3} .7868779
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2}-.1339412{col 26}{space 2} .1393961{col 37}{space 1}   -0.96{col 46}{space 3}0.337{col 54}{space 4}-.4071525{col 67}{space 3} .1392701
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2} .0866107{col 26}{space 2} .8597419{col 37}{space 1}    0.10{col 46}{space 3}0.920{col 54}{space 4}-1.598452{col 67}{space 3} 1.771674
{txt}{space 8}time {c |}{col 14}{res}{space 2} 3.389782{col 26}{space 2} .9089749{col 37}{space 1}    3.73{col 46}{space 3}0.000{col 54}{space 4} 1.608224{col 67}{space 3}  5.17134
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.0903201{col 26}{space 2} .0270645{col 37}{space 1}   -3.34{col 46}{space 3}0.001{col 54}{space 4}-.1433655{col 67}{space 3}-.0372746
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-.0145206{col 26}{space 2} .3896774{col 37}{space 1}   -0.04{col 46}{space 3}0.970{col 54}{space 4}-.7782743{col 67}{space 3}  .749233
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-32.58933{col 26}{space 2} 7.577181{col 37}{space 1}   -4.30{col 46}{space 3}0.000{col 54}{space 4}-47.44033{col 67}{space 3}-17.73833
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 261 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF ui XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-144.91382}  
Iteration 1:{space 3}log likelihood = {res:-125.11359}  
Iteration 2:{space 3}log likelihood = {res:-112.71887}  
Iteration 3:{space 3}log likelihood = {res:-108.15678}  
Iteration 4:{space 3}log likelihood = {res:-107.03084}  
Iteration 5:{space 3}log likelihood = {res:-107.00001}  
Iteration 6:{space 3}log likelihood = {res:-106.99997}  
Iteration 7:{space 3}log likelihood = {res:-106.99997}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,238
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     75.83
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-106.99997{txt}{col 49}Pseudo R2{col 67}= {res}    0.2616

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          ui{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2}  .344753{col 26}{space 2} 1.929422{col 37}{space 1}    0.18{col 46}{space 3}0.858{col 54}{space 4}-3.436845{col 67}{space 3} 4.126351
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2} 2.883148{col 26}{space 2} 1.883016{col 37}{space 1}    1.53{col 46}{space 3}0.126{col 54}{space 4}-.8074954{col 67}{space 3} 6.573791
{txt}{space 5}per100k {c |}{col 14}{res}{space 2} .0207015{col 26}{space 2}  .045289{col 37}{space 1}    0.46{col 46}{space 3}0.648{col 54}{space 4}-.0680633{col 67}{space 3} .1094663
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2}-.0489524{col 26}{space 2} .0395135{col 37}{space 1}   -1.24{col 46}{space 3}0.215{col 54}{space 4}-.1263974{col 67}{space 3} .0284926
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2}-.0559975{col 26}{space 2}  .817095{col 37}{space 1}   -0.07{col 46}{space 3}0.945{col 54}{space 4}-1.657474{col 67}{space 3} 1.545479
{txt}{space 8}time {c |}{col 14}{res}{space 2} 1.581603{col 26}{space 2} .5120334{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .5780359{col 67}{space 3}  2.58517
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.0338262{col 26}{space 2} .0124529{col 37}{space 1}   -2.72{col 46}{space 3}0.007{col 54}{space 4}-.0582335{col 67}{space 3}-.0094189
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-1.681071{col 26}{space 2} .7419982{col 37}{space 1}   -2.27{col 46}{space 3}0.023{col 54}{space 4} -3.13536{col 67}{space 3} -.226781
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -20.4865{col 26}{space 2} 5.286623{col 37}{space 1}   -3.88{col 46}{space 3}0.000{col 54}{space 4}-30.84809{col 67}{space 3}-10.12491
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 144 failures and 0 successes completely determined.{p_end}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF childcare XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-100.11011}  
Iteration 1:{space 3}log likelihood = {res:-87.369746}  
Iteration 2:{space 3}log likelihood = {res:-81.343581}  
Iteration 3:{space 3}log likelihood = {res: -80.12492}  
Iteration 4:{space 3}log likelihood = {res:-79.692332}  
Iteration 5:{space 3}log likelihood = {res: -79.68557}  
Iteration 6:{space 3}log likelihood = {res: -79.68556}  
Iteration 7:{space 3}log likelihood = {res: -79.68556}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,367
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     40.85
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -79.68556{txt}{col 49}Pseudo R2{col 67}= {res}    0.2040

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   childcare{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2}-1.760691{col 26}{space 2} 2.708194{col 37}{space 1}   -0.65{col 46}{space 3}0.516{col 54}{space 4}-7.068655{col 67}{space 3} 3.547272
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2} .8370416{col 26}{space 2} 2.374452{col 37}{space 1}    0.35{col 46}{space 3}0.724{col 54}{space 4}-3.816799{col 67}{space 3} 5.490882
{txt}{space 5}per100k {c |}{col 14}{res}{space 2}-.0082767{col 26}{space 2} .0247775{col 37}{space 1}   -0.33{col 46}{space 3}0.738{col 54}{space 4}-.0568397{col 67}{space 3} .0402863
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2} .0045784{col 26}{space 2} .0103076{col 37}{space 1}    0.44{col 46}{space 3}0.657{col 54}{space 4}-.0156241{col 67}{space 3}  .024781
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2} .2113457{col 26}{space 2} 1.057187{col 37}{space 1}    0.20{col 46}{space 3}0.842{col 54}{space 4}-1.860703{col 67}{space 3} 2.283394
{txt}{space 8}time {c |}{col 14}{res}{space 2} .9732378{col 26}{space 2}  .598752{col 37}{space 1}    1.63{col 46}{space 3}0.104{col 54}{space 4}-.2002947{col 67}{space 3}  2.14677
{txt}{space 6}timesq {c |}{col 14}{res}{space 2} -.018533{col 26}{space 2} .0137395{col 37}{space 1}   -1.35{col 46}{space 3}0.177{col 54}{space 4} -.045462{col 67}{space 3} .0083959
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-1.798773{col 26}{space 2} 1.041302{col 37}{space 1}   -1.73{col 46}{space 3}0.084{col 54}{space 4}-3.839687{col 67}{space 3} .2421405
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-15.41967{col 26}{space 2} 6.423379{col 37}{space 1}   -2.40{col 46}{space 3}0.016{col 54}{space 4}-28.00926{col 67}{space 3}-2.830076
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX ANALYSIS OF eviction XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-91.185296}  
Iteration 1:{space 3}log likelihood = {res:-79.137041}  
Iteration 2:{space 3}log likelihood = {res:-70.824598}  
Iteration 3:{space 3}log likelihood = {res:-67.448002}  
Iteration 4:{space 3}log likelihood = {res:-65.992115}  
Iteration 5:{space 3}log likelihood = {res:-65.794872}  
Iteration 6:{space 3}log likelihood = {res:-65.792684}  
Iteration 7:{space 3}log likelihood = {res:-65.792684}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,344
{txt}{col 49}LR chi2({res}8{txt}){col 67}= {res}     50.79
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-65.792684{txt}{col 49}Pseudo R2{col 67}= {res}    0.2785

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    eviction{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}black2018 {c |}{col 14}{res}{space 2} 1.470615{col 26}{space 2} 2.915975{col 37}{space 1}    0.50{col 46}{space 3}0.614{col 54}{space 4}-4.244592{col 67}{space 3} 7.185822
{txt}{space 4}hisp2018 {c |}{col 14}{res}{space 2}-.1078098{col 26}{space 2} 3.279209{col 37}{space 1}   -0.03{col 46}{space 3}0.974{col 54}{space 4}-6.534941{col 67}{space 3} 6.319321
{txt}{space 5}per100k {c |}{col 14}{res}{space 2} -.016825{col 26}{space 2} .0823003{col 37}{space 1}   -0.20{col 46}{space 3}0.838{col 54}{space 4}-.1781305{col 67}{space 3} .1444806
{txt}{space 4}neighbor {c |}{col 14}{res}{space 2} .0072961{col 26}{space 2} .0105722{col 37}{space 1}    0.69{col 46}{space 3}0.490{col 54}{space 4}-.0134251{col 67}{space 3} .0280173
{txt}{space 2}popcon2016 {c |}{col 14}{res}{space 2} 3.411065{col 26}{space 2} 1.154257{col 37}{space 1}    2.96{col 46}{space 3}0.003{col 54}{space 4} 1.148764{col 67}{space 3} 5.673367
{txt}{space 8}time {c |}{col 14}{res}{space 2} 2.380783{col 26}{space 2} 1.063231{col 37}{space 1}    2.24{col 46}{space 3}0.025{col 54}{space 4} .2968879{col 67}{space 3} 4.464678
{txt}{space 6}timesq {c |}{col 14}{res}{space 2}-.0511836{col 26}{space 2} .0240794{col 37}{space 1}   -2.13{col 46}{space 3}0.034{col 54}{space 4}-.0983783{col 67}{space 3}-.0039889
{txt}{space 5}weekend {c |}{col 14}{res}{space 2}-1.846011{col 26}{space 2} 1.046007{col 37}{space 1}   -1.76{col 46}{space 3}0.078{col 54}{space 4}-3.896147{col 67}{space 3} .2041246
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-31.43533{col 26}{space 2} 11.72627{col 37}{space 1}   -2.68{col 46}{space 3}0.007{col 54}{space 4}-54.41841{col 67}{space 3}-8.452254
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 329 failures and 0 successes completely determined.{p_end}

{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\User\Downloads\coronavirusstatelaws\205analysis_output20200330.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}30 Mar 2020, 23:14:54
{txt}{.-}
{smcl}
{txt}{sf}{ul off}